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* CS and IT world has changed a lot. New degrees have emerged. I am going to add data from 2017/18 admission season by October 2018. Till then promote and share this answer.*Let's set your thinking first.The Grad School Statistics We Never Hadhttp://occamstypewriter.org/scurry/2017/05/16/university-rankings-are-fake-news/Academic Rankings Considered Harmful!Where you went to college doesn't matter. https://www.weforum.org/agenda/2017/06/where-you-went-to-college-doesnt-matter-this-is-why?utm_content=bufferbb6ab&utm_medium=social&utm_source=facebook.com&utm_campaign=bufferMany students start their college research with rankings. That’s all well and good. You’ve got to start somewhere. But overall there is NO ranking system, NO acceptance criteria, no matter how perfect, is going to be able to tell you what university is best for your future. Graduate program prestige is a touchy subject for many people. I recommend that students look holistically, by looking at many rankings and university prestige, cost-benefit analysis, curriculum, post graduation job status, research fit, reputation of advisers etc. Of course you’d like to attend the program with the most prestige. But what if that prestigious university you’re in love with is price gouging? What if you’ll have to set back your life plans to be able to afford tuition, never mind the cost of living?Holistic view of the ranks:Look at different sources before settling in one ranking method.Research interests, fit with the adviser and adviser's reputation in the field (I cannot stress enough how important this is to any PhD applicants. #1 priority over anything. PeriodARWU: Academic Ranking of World Universities in Computer Science - 2015 (Helpful to PhD applicants: based on citations, research, impact factor. Much better than USNEWS for science, tech, CS ranking)NSF grant: Universities Report Highest-Ever R&D Spending of $65 Billion in FY 2011 (Helpful to PhD applicants, refer Table 3; Gives you an idea about research expenditures of the school - you want to end up in a college with continuous supply of fund)National Research Council: NRC Rankings Overview: Computer Sciences (Helpful to PhDs, sort by 'Research high'. This shows the quality of research.) Page on phd.org is derived from the NRC ranking.Microsoft Research rank: Page on bit.ly (Click the link or Copy paste the link, Click the field of your research on left, In the middle pane click 'see more ' in top organizations in [your field], Choose '5 years', and then sort by 'North America' or your continents).CSrankings.org, a ranking based on top-tier publication output of CS faculty. Unlike US News and World Report's approach, which is exclusively based on surveys, this ranking is entirely metrics-based. It measures the number of publications by faculty that have appeared at the most selective conferences in each area of computer science. However , this does not capture all top conferences for a particular field , so the ranking is based only on top 3–5 conferences. So, there are flaws in rankings particularly in algorithms, systems, HCI etc. But all rankings have them. Good as a preliminary filter to find faculty working on each field at each school.And finally, USNews Computer Science . Unfortunately many applicants and early career assistant professors use it as a primary filter. Comparing schools based only on USNews rank is a common mistake by PhD applicants. Academics don't look at this ranking highly. This is the baseless , subjective, and perception based, yet most common ranking system out there. Be careful.QS University rankings: Page on topuniversities.com [The research methodology is mostly subjective based. I recommend using this only for Masters and Business programs, not for PhD). In all honesty, QS and THE rankings overvalue European universities. But no one actually cares about it.(CAUTION- academic rankings are bad) Academic Rankings Considered Harmful!Do I want a Masters or a PhD ?For those who want to go on to graduate study, the first decision is whether to pursue a master’s degree or a PhD. The master’s degree usually consists of additional coursework and will give you a stronger foundation of the same sort you had as an undergraduate. Getting a PhD. is a MUCH LONGER/MUCH HARDER commitment (often five or more years), the core of which is an independent research project leading to a doctoral dissertation, and job in academic institutions or research fields.Is it easier to get admitted as a Masters compared to a PhD?It depends how you define "easier". There is no 'yes' or 'no' answer to this. Generally speaking, all applicants should be aware that the selection process is comprehensive and rigorous for PhD admission compared to Masters since there are generally fewer slots for PhDs, and Masters slots are typically not funded (vs most PhD students being fully funded).Money and degree?Sadly in today economy the ability for a student to pay full tuition has become a factor in some admissions decisions. MBA is notoriously known for “rich gets it all”. But this has definitely been the case in CS and IT in University of California, Georgia Tech, which has seen a rise in admitted applicants. In today marketplace, more and more schools are paying great attention to full paid Masters applicants that explained why so many campuses are packed by international students. This puts deserved and talented students behind the wealthy ones.Masters programs may be easier to get into if for no other reason than because you can pay tuition. Eg, University of Southern California, Georgia Tech Masters, University of Pennsylvania, Harvard (extension schools, professional school, and few Master degrees), Dartmouth, Cornell, Stanford, CMU etc. If the question is whether or not one's ability to pay can overcome deficiencies in one's transcript, the answer is "usually" no. The college will not allow an unqualified applicant to get in, but if there are two candidates, and one is high need (smart) and the other is not (slightly less smart), all other things being equal, the full pay student may be the one getting that fat envelope. This is one of the reasons why you see more Master students than PhD students in any schools. PhD programs are more difficult to gain acceptance to because you also receive a salary, health insurance and somebody in the nebulous world of academia pays your tuition (training grants, PI's grants, fellowships etc). The bar for any PhD school is much tougher than bar for any Masters. Example, it may be equally harder or if not more, to get into a top 30–35 PhD school than Masters at a top 5–10 school. Admission is overly critical and competitive at PhD level, and being able to pay tuition has no influence in PhD admission process. Industries and Academics also look very highly of PhD candidates compared to Masters. In some sense, Masters is an advanced bachelors.To confirm my statement look at the data below.***acceptance rate does not translate to how good a school is in research. Acceptance rate is a factor how many students applied to how many slots are available. But that does show overall strength of the program. YOU be the decision maker***------------------------------------------------------------------------------------MIT EECS, MAThe admission rate of applicants to EECS at MIT is approximately 6%. They only have one application process and it is for the Master’s/PhD combined. There is no separate Master’s degree application.Acceptance Rate: 6.4% , 2778 applications and admitted 180 applicants for 2014-2015Source: Emailed [email protected], CAMS: 667 applications, 123 accepted, 92 enrolled (18.4% acceptance rate)PhD acceptance: This past year we had 692 applicants to our Ph.D. program. We accepted 71, with about 50 of them taking us up on our offer. Now 10% might not seem like terrible odds as compared with, say, getting into Stanford as an undergraduate (7% admission rate). But those 692 applicants were already a somewhat self-selected group.Acceptance Rate: 18.4% (MS), 10.26% (PhD)Source: http://cs.stanford.edu/newsletter/past-newsletters/2011(Look for admissions statistics section)Princeton, NJAcceptance: 11 % They do not have statistics for computer science alone.Source: Look at graduate admissions for school of engineering and applied science: A Princeton Profile . Also emailed at [email protected] Tech (CS/HCI/OMS), GASource: Graduate Admissions - Table 4.3Page on gatech.eduAs you can see from first link, the admission rate is around 19% - 30%.PhD in GTECH is way harder than Masters to get admission. Impossible to compare quality of applicants at these two levels.Regular Masters CS with thesis option: As you can see that GTech Masters program is not as competitive to get into (Refer to IInd link). There are 3x to 5x more Masters students than PhDs at GTech. That is a quite significant difference and should tell something about quality of PhD students vs Masters students to get into. Email source says PhD admission rate is 10%.Masters in Interactive Computing/HCI: Total applicants: 350 applicants, Admit: 100 admits, and Enrolled: 50 . Only 50% enrolled. About half of students in Interactive Computing track; the rest are divided among the Psychology, Industrial Design, and Digital Media tracks. The acceptance rate is somewhat lower in the Interactive Computing track, but not significantly. Usually unfunded admission in Masters.Acceptance rate: 28.57%Source: Emailed [email protected] Masters: They also have an online Masters in CS program with Udacity. Acceptance Rate for OMS CS: 50% - 60%[Their on-site/in-person program is ranked top 10 by USNews, NOT the online program]Source: Emailed [email protected], ILEach year the Department of Computer Science at Illinois receives around 1500 applications for the MS and PhD programs and admits around 130 recruits between the two programs.Acceptance Rate (MS + PhD combined) : 8.66%Source: Application Evaluation ProcessWisconsin-Madison, WIAcceptance Rate: 20% (MS + PhD combined)Enrollment rate: only 36%Source: http://grad.wisc.edu/education/academicprograms/profiles/229.pdfUT-Austin, TXMS/PhD: ~ 20%. Nearly the same as Wisconsin Madison (MS + PhD combined)Source: [email protected] replied back they are as close to the numbers ~15-20%.Purdue, INFor Fall 2014 we had about 1112 applications for about 82 slots. For Fall 2013 we had about 980 applications for about 54 slots.Acceptance Rate: 7.3% (MS + PhD combined)Source: https://www.cs.purdue.edu/graduate/admission/process.htmlPurdue also has a CIT (computer information technology) degree with very high acceptance rate and a late deadline. But you may be required to pay a lot as a Masters.Harvard, MAAdmits about 8%-9% of applications across their graduate programs. They do not offer admission into the masters degree in Computer Science- at this time they only admit into their PhD program.For the class of graduate students entering in Fall 2014, SEAS received more than 2000 applications across all Ph.D. and master's programs and accepted just under 10 %Source: Emailed [email protected] Mellon University, PACarnegie Mellon overall is hovering around 15-20% (MS + PhD combined). Surprised (too many CS specializations)?? However, the School of Computer Science PhD only is about 6.8% (2012 Statistics: 5071 applicants, 345 admitted, 138 enrolled)The thing you have to note is that every computing specializations within Carnegie Mellon School of Conputing has different requirements and thus different acceptance rates.The admission intake is pretty high at Masters level - a bit higher than peer schools. Is Carnegie Mellon's School of Computer Science easier to get into thancomparative programs at top tier schools?Tip:CMU Heinz is relatively very easier to get into for Information Systems degree (but does not enjoy as much reputation as CS)Few (not all) masters programs at CMU are easier to get into for no other reason than because you can pay tuition as long as you meet minimum criteria for admission.CMU has a INI school focused at information technology, networking, security and technology management. Very good job placement but you may be paying atleast USD 80k-120k for your masters without any scholarship.Penn State CS / IST, PAabout 800-1000 applications for fall semester; about 50-75 applications for spring semester. We accept about 30-50 students for fall and about 6 for spring; most of these are PHD students.Acceptance Rate: 6.25% (fall, MS + PhD combined) ; 12% springSource: Graduate Admissions and emailed [email protected] Science and Technology department: Penn State has a highly reputed interdisciplinary department- CS, Sociology, and Psychology mixed together.M.S. Program | College of Information Sciences and TechnologyUniversity of Pennsylvania CIS/CIT, PAPhD in CIS/CIT : 448 applicants to the doctoral program, 50 candidates admittedAcceptance Rate: 11.16%Masters program in CS : 752 applicants, 135 candidates admittedAcceptance Rate: 17.95%[No Aid for Masters "cash cow' masters program]Masters program in IT: 331 applicants, 58 candidates admittedAcceptance Rate: 17.52%Source for all above: Graduate Program Admissions Statistics[No Aid for Masters "cash cow' masters program]Brown University, RIPhD: 300 applications to our PhD programAcceptance Rate: 16%Masters: About 375 applicationsAcceptance Rate: 22%Source: Emailed [email protected][Masters in CS is relatively easier to get into even though it is an Ivy - a "cash cow" masters program]Cornell University, NYPhD: About 11% for the fall 2015 for both CS and iSchool eachSource: Emailed [email protected] University, NYPhD: 710 PhD applicants and 53 admits for fall 2015 Acceptance Rate: 7.46%MS: MS is relatively easier to get into, higher acceptance rate and does not have financial aid. 'cash cow' masters program.Source: Emailed admission committee at [email protected] Ann Arbor(CS/iSchool), MICS/CE: 618 PhD applications for 64 slots. Masters is higher acceptance rate.Acceptance Rate: 10.35%Source: Computer Science and EngineeringInformation Science: 8.27%Acceptance:145 PhD applications for 12 slots - 5 years averageSource: Rackham Graduate SchoolDuke University, NCPhD and MS about 17 % (As you can see the GRE and GPA criteria for Masters admission is lower than peer schools)Source: Computer Science - Duke UniversityDuke Graduate School (more statistics)Yale University, CTAdmission rate of PhD: ~20% (according to an email response) but the link below says 12%Masters: MS program is course work only and unfunded.Source: Department of Computer Science - Yale University in New Haven, CT - Graduate Program Information at Petersons.comAlso emailed cs office at Yale.University of Washington (CS/iSchool/HCDE), WACS: Over 1400 applications and admitted 150 students. Only 56 PhD students in 2014-2015 cohort. Over the past 10 years or so, the acceptance rate has been about 10%.Graduate School StatisticsEnroll rate: 33%. Typically about 1/3 of the students they admit end up comingSource: grad-admissions@cs.washington.edu---------------------------------------------------------------------------------HCDE (recently established program): For fall 2015, there were total of 86 PhD applications that admitted 7 students.PhD Acceptance rate:8.13%Master’s program received 484 applications and admitted 93 students. Acceptance rate: 19.21%Note: Heavily design and UX oriented, and prototyping based----------------------------------------------------------------------------------iSchool:Admit rate for the PhD program is normally around 15-20%Masters (MSIM) programs are less selective and does not enjoy much reputation. Their masters is a cash cow. However, their PhD is competitive.Acceptance Rate: 23% for MastersSource: Page on uw.eduUniversity of Maryland, College Park (CS/iSchool), MDAcceptance Rate: Overall about 20% of applicants are admitted, and about 1/3rd of them enrollSource: Emailed [email protected] for Prospective StudentsiSchool PhD: ~20%iSchool Masters: See below.iSchool MIM: over 600 applications and admitted just over 100 applicants: 16.66%iSchool HCIM: accepted 60 out of 111 applications, 54.4% [Easy Safety. Do not rush because of the Maryland name. Make sure you check available courses, TA/RA opportunities and industry reaction to this degree]Source: Page on umd.edu and emailed [email protected] Berkeley, CAFor EECS overall, not broken down by degree: "3100 applicants for about 100 slots". Their yield is probably high. They also say the MS CS program "admits very few students."Overall PhD and MS combined: <5%Source: Facts and figuresThey also have an interdisciplinary iSchool. Lower acceptance rate compared to their CS department due to the interdisciplinary nature and high demand of the program. Admits only 5–8 PhDs per year out of several hundred applications. Ph.D. Application InstructionsUniversity of Southern California, CAAcceptance Rate: No [email protected] responded that they do not have that statistic available.[Probably one of the easiest schools among top tiers, to get into for Masters with full pay.]University of California Davis, CAAdmission to the Graduate Group in Computer Science is highly competitive. On average, we receive over 1,000 applications for admission and generally admit the top 10%.Acceptance Rate:: ~10%Source: Prospective Graduate Students - Computer ScienceUniversity of California, Los Angeles, CAAcceptance Rate: 22%Source: Page on ucla.edu(The new data suggests acceptance is lower than this)University of California, San Diego,CAAcceptance Rate for MS: For fall 2015, 900 MS applicants, acceptance rate of 7.5%,Acceptance Rate for PhD: 375 PhD applicants with an admission percentage of 19%(Notice the higher PhD acceptance compared to Masters. This is because UCSD is a top tier research school and usually focus more on PhDs)University of California, Santa Barbara, CAAcceptance Rate: ~ 10% for PhDs. More for Masters. We receive around 400+ PhD applications per year and admit between 30-50 students. Our goal is to have roughly 20-25 students join the program each Fall.Source: Frequently Asked Questions for UCSB Graduate AdmissionsCaltech, CAAcceptance Rate: Still searchingJohns Hopkins, MDAcceptance Rate: Still searching

To me the best answer for this question was since been deleted by anon. Fortunately I liked the answer so much that I saved it locally and printed it. Hence I am posting this again, word to word as answered by Anon.So I have written this like the advice I would give myself if I could travel back in time or what I really hope to see in the undergrads I want to hire. I hope you don't get discouraged/put off.First thing: Solidworks/ProE/AutoCAD/Rhino/Blender/CATIA and GD&T are not skills for degree'd engineers. You don't do a BS/ME for draftsmanship. It's like putting MS Office on your resume. You can pick that skill up on your own time.Second thing: I am talking about becoming an engineer here. You know, the kind that build rockets and microengines (Sandia MEMS Home Page). I have nothing against grades, but I don't care very much for them. So I am not talking about getting the best grades.Now. Here's what you need to acquire proficiency in through your 4-year BS0. Read wikipedia.1. Programming - Start with Matlab/Python. Then graduate to C++. An example of a programming goal would be to use this to create your own computational graphics engines. Why? Because this teaches you about visualizing vectors, arrays, transforms and leads you to higher-dimensional algebra. Make sure you can understand and implement Runge Kutta family of algorithms before you think you are done. A recommendation would be to ditch Windows and move to some flavor of Linux or Mac. You need to understand concepts behind batch/shell scripting and importing open source scripts to embed inside your own. If you don't do anything else in your freshman or sophomore years, that's fine. But make sure you master this.2. Linear algebra and differential equations - Now, most ME syllabi force the courses on you early on. But very few MEs truly understand these topics. This is the source of all ME theory. I CANNOT STRESS THIS ENOUGH! Most ME professors DO NOT understand linear algebra or its importance - they will fuck it up for you so you will be confused/avoid derivative topics forever. Don't take these courses offered inside your department - take them from CS or EE or Math professors. Or learn it from Gilbert Strang on Youtube. Tie this together with your programming to create numerical simulations. Do NOT take these courses until you are done with your programming.3. Statistics - Take this twice. Audit it as a freshman. Then take the course again as a senior. This will be the single most important course you ever take as a professional in any field.4. Engineering mathematics. The rest of your life depends on this. Pay attention to spatial transforms, Fourier analysis, Complex analysis, Potential theory, PDEs, Interpolation/curve fitting, optimization theory. Look for ways to implement these concepts using your programming skills. If you ever wonder about the usefulness of any of this, or you get the choice to skip a few topics - you are doing it wrong. Good engineers use these concepts EVERYDAY.5. Dynamics/Advanced dynamics - Take this in the Physics department. ME profs screw it up here again, they focus on the mechanics of algebraic manipulation and don't explain concepts very well. Your objective would be to be able to independently construct FBDs of complex interacting mechanisms, and generate classical non/autonomous, non/linear differential equations that describe the time-history of the system. Develop a familiarity with index notation and tensors and operator spaces. Your indicial programming experience will really help you here.6. Statics/Solid mechanics - Master Timoshenko Goodier/Theory of elasticity. Even if it takes you the rest of your life. If you got through point 2, you should be able to point out the inefficiency of the SFDs and BMDs and Mohr's circle concepts. Try visualizing the simple cases while cognizant that life is not simple. Use your programming finesse to program numerical solutions to your ODEs and equations.7. Vibration theory - If you actually got through point 2, you will find this a breeze. All they do here is study a second order, non/homogenous, non/autonomous non/dimensionalized ordinary differential equation and the effects of parametric variations (mkc, forcing frequency). If you got through 5, you should be able to figure out all the base excitation, seismic perturbation, isolation, rotating machinery concepts. If you got through 6, then plates/beam vibration problems. If you got through 2 & 4, you will be able to work through MDOF systems and all the modal analysis techniques. This is where you segue to coupled SHO/QHO concepts.8. Therodynamics/Fluidics - I am not the right person to advise on these topics. But they are pretty straightforward at the undergraduate level and mostly applications of differential equations and continuum mechanics.If you followed instructions so far, everything else is a straightforward application of what you should have learned by now. That's all you really need to be a degree'd mechanical engineer - math and physics. Everything else is a specialization and extension of domains from the presented fields into specific tasks. This is also where you start encountering professional jargon. And don't let terms/eponyms scare you off.Also mechanical engineers don’t generally design machines from scratch – hobbyists and mathematicians do. We follow standards for our industry, mix and match components, or use well defined algorithms to create a new one. There are concepts in kinematic chains, algebraic linkage synthesis and design that are used here. So sure you can read about gears and machinery and 4-bar linkages and cams and geneva wheels, but it is highly improbable that you, as an ME, will create one. It is more likely that a technician or a sheet metal worker will create something utterly brilliant. So if that’s what you want to do, figure on grad school. You can however use your solid mechanics skills to design the components to withstand pyrotechnic impacts.I skip over manufacturing and 'product engineering' classes because they are shit, when taught in school. You can't master manufacturing sitting in a class, and you certainly are never going to learn enough in school about how to design a full product. Those axiomatic design principles and synectics and product lifecycle management and ideation and Gantt charts and brainstorming processes are bullshit. Nobody in real life does that. Those who do, are not engineers. If you really want to understand manufacturing, skim through Manufacturing Processes for Design Professionals: Rob Thompson: 9780500513750: Amazon.com: Books, then go talk with people on shop floors, or watch how it's made on Youtube. If you really want to understand the product design process, follow Kickstarter h/w startup stories.Do not ever waste your time on survey or presentation courses. Avoid attending school seminars if you are not interested in the topic. You should attend all seminars that promise to show you math or process or cool videos. You want to keep an ear out for examples and case studies that show explicit details of how systems get modeled/implemented using math or experiments. Avoid 'design' seminars (usually a peddler from Wharton or Sloan or Kellog) - they are pretty, but pointless.Take all lab classes you can. ALL of them. All you can afford. Pottery too, if you have that option. Just drop in to watch other people work if you got the free time. Pottery as well. Use the equipment there till you break it - You are paying for it anyway. Make all the mistakes you can ever imagine there. AND DON'T FUCK AROUND IN THE MACHINE SHOP BRO!!!Amongst other advice, find a PhD student about to graduate every year and get them to mentor you. Don’t believe in that ‘I am busy’ crap – they all are usually on Quora or editing Wikipedia anyway. I speak from experience. Pick people from diverse fields – machine learning, operations optimization, public policy, neurobiology, kernel development … You want to understand what they do, how they do it, what they use to do it and create a possible job network. You don’t want seniors to mentor you because, unless they go to grad school, they will never be in any position to introduce you to great opportunities on time scales relevant to your interests.Now, let's talk about being a professional mechanical engineer9. Read ISO/ASME/ASTM/ASTC/ASMI (standards organizations) standard practices. That's the only place where they really tell you how theory meets practice. If you believe your university doesn't provide you access to those - Sue them! Beg/borrow/steal. Whatever. But if you really want to know how things are done; Read the standards. Not the website and their discussion forums. Read the standards.10. Take/Audit courses on electromagnetism, digital electronics, electrical theory, VLSI/Silicon based designs, electrical machinery. You should be able to design your own motor driver/filter/power regulator/multivibrator circuits and implement them on PCBs. Start dipping into embedded microcontrollers here. This is where you C++ experience should start paying off.11. Signal processing - Audio/image/Power signals - Master the topic of discrete Fourier transforms/spectral densities and how they are used and calculated. Figure out how digital sampling and digital filters work and how filters and masks get designed. Move on to z-transforms and recursive filters. Your statistics background starts to become useful here. At least figure out how to manipulate images using pixel-array math.12. Control systems - THIS ties up everything. And THIS was the topic that really got you into ME. You didn't join ME to make bridges or prepare CAD layouts for GE ovens or tractor engines or boiler chambers for plants or be a grease monkey. You joined ME to make structures that move, intelligently. If you have done things right so far, this is where you will get to have fun. It ties together your dynamics and linear algebra first, then programming, signal processing and statistics next, finally you implement it all using your electronics/embedded skills.13. Instrumentation – People have equipment that costs between a thousand dollars to over several million. You need to learn how to use them, AND how to construct them. You will find that making equipment is always cheaper than buying a turnkey system from a manufacturer. So companies prefer to design/assemble their own systems. This should segue into design of experiments/statistical validation. Your goal should be to know how to hook up the hydraulic pressure gauge in an EMD F51PHI locomotive cab suspended 10 ft up in a shed to an office in Minnesota.Along with instrumentation, you will frequently need to develop software to control the instruments. Some people use labview, but with your mastery of C/matlab you will do better.If you want to get into finite elements, you can’t do that in undergrad. All you will learn is to push buttons. Most engineers only think they understand FEA – they actually don’t. It takes practice, study and experience. The pretty pictures don’t mean much by themselves. So I will say go to grad school or intern with a practicing consultant.That should about cover your basics and get you a good job. But if you want to get a great job, you will need professional degrees or exhibit skills in some of the following. So, on to specialization:1. Fracture/fatigue/materials on the nanoscale.2. MEMS – Look up Sandia National Labs/MEMS. Biggest opportunity for MEs since all companies are moving from RnD to ramping up production right about now. Micromachining and processing technologies research is active as well. MOEMS was hot, sensors are sizzling, actuators not so much, lab-on-chip was meandering about, last I checked. Significant effort underway on determining lifetime/reliability as well. People were excited about energy harvesting, but that seems to be toned down now. Lot’s of material science opportunities.3. Microfluidics – These guys blow bubbles through microchannels! Look up lab-on-a-chip.4. Bioengineering – Tissue printing/engineering! There’s also research on mechanical characterization of bio-materials (bones/ligaments/RBCs)5. Medical devices/robotics – da Vinci/intuitive. Also swallowable robots and cameras. Lots of health monitoring devices and OR assistants.6. Robotics/control systems – Typically, you need to be core CS/EE for this. They are the ones doing most of this research. But you can create opportunities for yourself by choosing to focus on dynamic structure design or kinematics or something on that order. Look up Hod Lipson/Cornell or Red Whittaker/CMU or Marc Raibert/ex CMU/MIT leg labs or Rob Wood/Harvard for inspiration. Google and Amazon have raised this field’s profile over the last couple of years. Look up compliant mechanisms/robots, autonomous vehicles, haptics, telepresence, Raytheon XOS II,... Lot’s of bullshit in the name of ‘assistive robotics’ (that no one can or will want to afford or use, and medicare won’t support).7. Control systems/avionics – I worked on optimizing damage-resilient, real-time coolant distribution through nuclear subs, my ex-boss worked on guidance systems for the Pershing/Hera systems. This is a mature engineering field at the moment (not much RnD) but scope for new applications.8. Thermo research – They do crazy things with combustion, not my domain.9. Nonlinear dynamics – Applied theory, predicting weather(?!), galloping (hopf) systems, .. this field goes on till quantum cryptography and then some.10. Aerospace vehicles – SpaceX. Etc. Vibrations theory, dynamical systems and controls. Your vibrations theory needs to be strongly coupled.11. Infrastructure – Given Keystone or fracking, infrastructure is going to undergo another massive boom.12. Petroleum - …13. FEA – Meshing and geometry algorithms, data compression, rendering are being researched14. Energy – fuel cell research, the cryptozoology equivalent in ME They’ve been at it for a while, but it seems to be a funding generation ploy.15. Marine systems - …16. Theoretical systems – Lots of work on rule based machine learning based design synthesis, structural optimization (back in early 2000’s it was all about simulated annealing and genetic algos, now they call it machine learning), dynamic self modeling, multi-agent systems,17. MAV/Flight dynamics – Concentrated around rotorcraft/flapping wing architectures. Mostly experimental, some theoretical research going on.18. ICE research – Very avoid!19. Tribology - Nonlinear dynamics of rate state dependent friction generate P/S/Love/Rayleigh wave phenomena used to predict earthquakes. Studying hydrodynamic lubrication of journal bearings is a trifle boring compared to that. See Ruina's work at Brown.Universities on the West and East coast typically work on the new frontiers of research, while the rest work on last-century concepts. So if you go to school in AK, you will find stuff on corrosion, rotor blades, missiles, defense, aerospace machining … But if you are in MA, you will find machine learning, robotics, vision, SLAM, MEMS, materials, algorithmic synthesis, complex systems etc.########################################I have written this like the "Survival guide for mechanical engineers on the journey to create astonishing engineering". This is written with North-American ADHD undergrads in mind. So I tend to be didactic, and, in the spirit of times, use hyperbole to signify importance (no selfies, however. Much disappoint.). I also abuse education professionals profusely - But that's only my personal experience – all the additional work I had to put in because courses were not designed right, or because a newly hired asst professor was in charge of a particular course that they had no experience in or because the lecturer, originally from Asia, had this distracting accent and circuitous description that just beat about the bush more than I could keep track of or maybe because most of the freshman/sophomore/introductory courses, specially non-core ME courses, are generally fanned out to temp staff/lecturers that generally don't know jackshit about how things are done or don’t care. So you see, personal failing on my part. That's my excuse for the abuse. And there's catharsis involved as well. So I apologize in advance.I have a BS/AME USC, and MS/MAE, UC system, PhD/ME (and RI+LTI+ECE) CMU. I wasn't a great student during my BS; 2.7 GPA, almost dropped out to be a professional musician. GRE 1600/6.0 happened. I joined the masters program because I was getting a fellowship+stipend. Programming happened. YouTube happened. OCW video content happened. I worked on projects with all or some of the following labs LLNL/SNL/LL MIT/NRLMRY/NECSI/SFI through my PhD. For your reference: MS/PhD GPA 3.6/3.8. No money, at the time of graduation. Now making some.Dear Anon, I don't know why you deleted the answer but to me its awesome advice, thank you very much. I would more than happy to take this off once you decide to post it yourselves.

I found this answer a while back by anonymous. This answer may be more suitable for advanced economies rather than India.EVERYTHING below this is not mine.So I have written this like the advice I would give myself if I could travel back in time or what I really hope to see in the undergrads I want to hire. I hope you don't get discouraged/put off.First thing: Solidworks/ProE/AutoCAD/Rhino/Blender/CATIA and GD&T are not skills for degree'd engineers. You don't do a BS/ME for draftsmanship. It's like putting MS Office on your resume. You can pick that skill up on your own time.Second thing: I am talking about becoming an engineer here. You know, the kind that build rockets and microengines (Sandia MEMS Home Page). I have nothing against grades, but I don't care very much for them. So I am not talking about getting the best grades.Now. Here's what you need to acquire proficiency in through your 4-year BS.0. Read Wikipedia.1. Programming - Start with Matlab/Python. Then graduate to C++. An example of a programming goal would be to use this to create your own computational graphics engines. Why? Because this teaches you about visualizing vectors, arrays, transforms and leads you to higher-dimensional algebra. Make sure you can understand and implement Runge-Kutta family of algorithms before you think you are done. A recommendation would be to ditch Windows and move to some flavour of Linux or Mac. You need to understand concepts behind batch/shell scripting and importing open source scripts to embed inside your own. If you don't do anything else in your freshman or sophomore years, that's fine. But make sure you master this.2. Linear algebra and differential equations - Now, most ME syllabi force the courses on you early on. But very few MEs truly understand these topics. This is the source of all ME theory. I CANNOT STRESS THIS ENOUGH! Most ME professors DO NOT understand linear algebra or its importance - they will fuck it up for you so you will be confused/avoid derivative topics forever. Don't take these courses offered inside your department - take them from CS or EE or Math professors. Or learn it from Gilbert Strang on Youtube. Tie this together with your programming to create numerical simulations. Do NOT take these courses until you are done with your programming.3. Statistics - Take this twice. Audit it as a freshman. Then take the course again as a senior. This will be the single most important course you ever take as a professional in any field.4. Engineering mathematics -The rest of your life depends on this. Pay attention to spatial transforms, Fourier analysis, Complex analysis, Potential theory, PDEs, Interpolation/curve fitting, optimization theory. Look for ways to implement these concepts using your programming skills. If you ever wonder about the usefulness of any of this, or you get the choice to skip a few topics - you are doing it wrong. Good engineers use these concepts EVERYDAY.5. Dynamics/Advanced dynamics - Take this in the Physics department. ME profs screw it up here again, they focus on the mechanics of algebraic manipulation and don't explain concepts very well. Your objective would be to be able to independently construct FBDs of complex interacting mechanisms, and generate classical non/autonomous, non/linear differential equations that describe the time-history of the system. Develop a familiarity with index notation and tensors and operator spaces. Your indicial programming experience will really help you here.6. Statics/Solid mechanics - Master Timoshenko Goodier/Theory of elasticity. Even if it takes you the rest of your life. If you got through point 2, you should be able to point out the inefficiency of the SFDs and BMDs and Mohr's circle concepts. Try visualizing the simple cases while cognizant that life is not simple. Use your programming finesse to program numerical solutions to your ODEs and equations.7. Vibration theory - If you actually got through point 2, you will find this a breeze. All they do here is study a second order, non/homogenous, non/autonomous non/dimensionalized ordinary differential equation and the effects of parametric variations (mkc, forcing frequency). If you got through 5, you should be able to figure out all the base excitation, seismic perturbation, isolation, rotating machinery concepts. If you got through 6, then plates/beam vibration problems. If you got through 2 & 4, you will be able to work through MDOF systems and all the modal analysis techniques. This is where you segue to coupled SHO/QHO concepts.8. Thermodynamics/Fluidics - I am not the right person to advise on these topics. But they are pretty straightforward at the undergraduate level and mostly applications of differential equations and continuum mechanics.If you followed instructions so far, everything else is a straightforward application of what you should have learned by now. That's all you really need to be a degree'd mechanical engineer - math and physics. Everything else is a specialization and extension of domains from the presented fields into specific tasks. This is also where you start encountering professional jargon. And don't let terms/eponyms scare you off.Also mechanical engineers don’t generally design machines from scratch – hobbyists and mathematicians do. We follow standards for our industry, mix and match components, or use well defined algorithms to create a new one. There are concepts in kinematic chains, algebraic linkage synthesis and design that are used here. So sure you can read about gears and machinery and 4-bar linkages and cams and geneva wheels, but it is highly improbable that you, as an ME, will create one. It is more likely that a technician or a sheet metal worker will create something utterly brilliant. So if that’s what you want to do, figure on grad school. You can however use your solid mechanics skills to design the components to withstand pyrotechnic impacts.I skip over manufacturing and 'product engineering' classes because they are shit, when taught in school. You can't master manufacturing sitting in a class, and you certainly are never going to learn enough in school about how to design a full product. Those axiomatic design principles and synectics and product lifecycle management and ideation and Gantt charts and brainstorming processes are bullshit. Nobody in real life does that. Those who do, are not engineers. If you really want to understand manufacturing, skim through Manufacturing Processes for Design Professionals by Rob Thompson, then go talk with people on shop floors, or watch how it's made on Youtube. If you really want to understand the product design process, follow Kickstarter h/w startup stories.Do not ever waste your time on survey or presentation courses. Avoid attending school seminars if you are not interested in the topic. You should attend all seminars that promise to show you math or process or cool videos. You want to keep an ear out for examples and case studies that show explicit details of how systems get modeled/implemented using math or experiments. Avoid 'design' seminars (usually a peddler from Wharton or Sloan or Kellog) - they are pretty, but pointless.Take all lab classes you can. ALL of them. All you can afford. Pottery too, if you have that option. Just drop in to watch other people work if you got the free time. Pottery as well. Use the equipment there till you break it - You are paying for it anyway. Make all the mistakes you can ever imagine there. AND DON'T FUCK AROUND IN THE MACHINE SHOP BRO!!!Amongst other advice, find a PhD student about to graduate every year and get them to mentor you. Don’t believe in that ‘I am busy’ crap – they all are usually on Quora or editing Wikipedia anyway. I speak from experience. Pick people from diverse fields – machine learning, operations optimization, public policy, neurobiology, kernel development … You want to understand what they do, how they do it, what they use to do it and create a possible job network. You don’t want seniors to mentor you because, unless they go to grad school, they will never be in any position to introduce you to great opportunities on time scales relevant to your interests.Now, let's talk about being a professional mechanical engineer9. Read ISO/ASME/ASTM/ASTC/ASMI (standards organizations) standard practices. That's the only place where they really tell you how theory meets practice. If you believe your university doesn't provide you access to those - Sue them! Beg/borrow/steal. Whatever. But if you really want to know how things are done; Read the standards. Not the website and their discussion forums. Read the standards.10. Take/Audit courses on electromagnetism, digital electronics, electrical theory, VLSI/Silicon based designs, electrical machinery. You should be able to design your own motor driver/filter/power regulator/multivibrator circuits and implement them on PCBs. Start dipping into embedded microcontrollers here. This is where you C++ experience should start paying off.11. Signal processing - Audio/image/Power signals - Master the topic of discrete Fourier transforms/spectral densities and how they are used and calculated. Figure out how digital sampling and digital filters work and how filters and masks get designed. Move on to z-transforms and recursive filters. Your statistics background starts to become useful here. At least figure out how to manipulate images using pixel-array math.12. Control systems - THIS ties up everything. And THIS was the topic that really got you into ME. You didn't join ME to make bridges or prepare CAD layouts for GE ovens or tractor engines or boiler chambers for plants or be a grease monkey. You joined ME to make structures that move, intelligently. If you have done things right so far, this is where you will get to have fun. It ties together your dynamics and linear algebra first, then programming, signal processing and statistics next, finally you implement it all using your electronics/embedded skills.13. Instrumentation – People have equipment that costs between a thousand dollars to over several million. You need to learn how to use them, AND how to construct them. You will find that making equipment is always cheaper than buying a turnkey system from a manufacturer. So companies prefer to design/assemble their own systems. This should segue into design of experiments/statistical validation. Your goal should be to know how to hook up the hydraulic pressure gauge in an EMD F51PHI locomotive cab suspended 10 ft up in a shed to an office in Minnesota.Along with instrumentation, you will frequently need to develop software to control the instruments. Some people use labview, but with your mastery of C/matlab you will do better.If you want to get into finite elements, you can’t do that in undergrad. All you will learn is to push buttons. Most engineers only think they understand FEA – they actually don’t. It takes practice, study and experience. The pretty pictures don’t mean much by themselves. So I will say go to grad school or intern with a practicing consultant.That should about cover your basics and get you a good job. But if you want to get a great job, you will need professional degrees or exhibit skills in some of the following. So, on to specialization:1. Fracture/fatigue/materials on the nanoscale.2. MEMS – Look up Sandia National Labs/MEMS. Biggest opportunity for MEs since all companies are moving from RnD to ramping up production right about now. Micromachining and processing technologies research is active as well. MOEMS was hot, sensors are sizzling, actuators not so much, lab-on-chip was meandering about, last I checked. Significant effort underway on determining lifetime/reliability as well. People were excited about energy harvesting, but that seems to be toned down now. Lot’s of material science opportunities.3. Microfluidics – These guys blow bubbles through microchannels! Look up lab-on-a-chip.4. Bioengineering – Tissue printing/engineering! There’s also research on mechanical characterization of bio-materials (bones/ligaments/RBCs)5. Medical devices/robotics – da Vinci/intuitive. Also swallowable robots and cameras. Lots of health monitoring devices and OR assistants.6. Robotics/control systems – Typically, you need to be core CS/EE for this. They are the ones doing most of this research. But you can create opportunities for yourself by choosing to focus on dynamic structure design or kinematics or something on that order. Look up Hod Lipson/Cornell or Red Whittaker/CMU or Marc Raibert/ex CMU/MIT leg labs or Rob Wood/Harvard for inspiration. Google and Amazon have raised this field’s profile over the last couple of years. Look up compliant mechanisms/robots, autonomous vehicles, haptics, telepresence, Raytheon XOS II,... Lot’s of bullshit in the name of ‘assistive robotics’ (that no one can or will want to afford or use, and medicare won’t support).7. Control systems/avionics – I worked on optimizing damage-resilient, real-time coolant distribution through nuclear subs, my ex-boss worked on guidance systems for the Pershing/Hera systems. This is a mature engineering field at the moment (not much RnD) but scope for new applications.8. Thermo research – They do crazy things with combustion, not my domain.9. Nonlinear dynamics – Applied theory, predicting weather(?!), galloping (hopf) systems, .. this field goes on till quantum cryptography and then some.10. Aerospace vehicles – SpaceX. Etc. Vibrations theory, dynamical systems and controls. Your vibrations theory needs to be strongly coupled.11. Infrastructure – Given Keystone or fracking, infrastructure is going to undergo another massive boom.12. Petroleum - …13. FEA – Meshing and geometry algorithms, data compression, rendering are being researched14. Energy – fuel cell research, the cryptozoology equivalent in ME They’ve been at it for a while, but it seems to be a funding generation ploy.15. Marine systems - …16. Theoretical systems – Lots of work on rule based machine learning based design synthesis, structural optimization (back in early 2000’s it was all about simulated annealing and genetic algos, now they call it machine learning), dynamic self modeling, multi-agent systems,17. MAV/Flight dynamics – Concentrated around rotorcraft/flapping wing architectures. Mostly experimental, some theoretical research going on.18. ICE research – Very avoid!19. Tribology - Nonlinear dynamics of rate state dependent friction generate P/S/Love/Rayleigh wave phenomena used to predict earthquakes. Studying hydrodynamic lubrication of journal bearings is a trifle boring compared to that. See Ruina's work at Brown.Universities on the West and East coast typically work on the new frontiers of research, while the rest work on last-century concepts. So if you go to school in AK, you will find stuff on corrosion, rotor blades, missiles, defense, aerospace machining … But if you are in MA, you will find machine learning, robotics, vision, SLAM, MEMS, materials, algorithmic synthesis, complex systems etc.I have written this like the "Survival guide for mechanical engineers on the journey to create astonishing engineering". This is written with North-American ADHD undergrads in mind. So I tend to be didactic, and, in the spirit of times, use hyperbole to signify importance (no selfies, however. Much disappoint.). I also abuse education professionals profusely - But that's only my personal experience – all the additional work I had to put in because courses were not designed right, or because a newly hired asst professor was in charge of a particular course that they had no experience in or because the lecturer, originally from Asia, had this distracting accent and circuitous description that just beat about the bush more than I could keep track of or maybe because most of the freshman/sophomore/introductory courses, specially non-core ME courses, are generally fanned out to temp staff/lecturers that generally don't know jackshit about how things are done or don’t care. So you see, personal failing on my part. That's my excuse for the abuse. And there's catharsis involved as well. So I apologize in advance.I have a BS/AME USC, and MS/MAE, UC system, PhD/ME (and RI+LTI+ECE) CMU. I wasn't a great student during my BS; 2.7 GPA, almost dropped out to be a professional musician. GRE 1600/6.0 happened. I joined the master’s program because I was getting a fellowship & stipend. Programming happened. YouTube happened. OCW video content happened. I worked on projects with all or some of the following labs - LLNL/SNL/LL MIT/NRLMRY/NECSI/SFI through my PhD. For your reference: MS/PhD GPA 3.6/3.8. No money, at the time of graduation. Now making some.