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Found 11 results

  1. So the title is pretty self explanatory, but let me really explain what I'm trying to understand. As a prospective structural engineer, I wanted to know the difference between FEA and C.M. To be more specific, computational 'structural' mechanics, as opposed to comp. fluid mech. I have heard that FEA is fairly interdisciplinary, i.e. something that draws a lot from applied math and even computer science. So the question is - how is computational structural mechanics different. And is FEA really employed a lot in construction. I know that it's very useful in aerospace, but how about good ol buildings. cheers.
  2. Undergrad Institution: One of the NYS SUNY Schools Major(s): Math Minor(s): Atmospheric Science and History GPA: 2.58 overall/ 3.05 Math Type of Student: Domestic, Male, Hispanic Research area: Mostly an applied math person. ODE/PDE and complex analysis Research Experience: None Awards/Honors/Recognitions: In Recognition of your exemplary attitude and outstanding achievements as a student with a disability (Won the award twice) Pertinent Activities or Jobs: Math tutor, bagger at a supermarket Letters of Recommendation: None as of yet, Although I am looking at two professors who can backup reasoning as to why GPA is low. Math/Statistics Grades: Calculus 1 D (second attempt B), Calculus 2 B-, Calculus 3 (B), Ordinary Differential Equations A-, Partial Differential equations TBD, Linear Algebra TBD, Probability Theory TBD, Statistics TBD, Advanced Calculus 1 Fall 2020, Real Analysis C (summer course 8 weeks), Complex Variables B Any Miscellaneous Points that Might Help: Grad Atmospheric Chemistry (currently have an incomplete but I just submitted the assignment last week), I will be taking graduate level complex analysis this Fall. Also planning to sit in an Analysis seminar called "Spaces of analytic functions" I went to a community college and started in Intermediate Algebra and made my way to calculus 1 before I transfer. During my time at CC I had changed my major mulptic times because I wasn't sure what to do. At first I was interested in atmospheric science, Geology, Biology and chemistry. Whenever, I took the required classes I always saw myself focusing on math. I ended up transferring as a chemistry major because I was a chemistry major during that time. My first semester at SUNY, Fall 2017, started and I got my first F (Physics 1) which brought my GPA really low. Second semester I did better but organic chemistry 2 lecture was the only C- I got all other courses I was B or A that semester. In Fall 2018 I realized that I loved math more than any other subject. Now I am two semesters away from finishing. I am graduating in Spring 2021 Looking to take a 6 month or year break to study for my GRE and math GRE exam subject while I work at a library. Final Thoughts: 1. Is there anything I can do at this point? 2. I am taking three math courses over the summer 2020 (Partial Differential equations TBD, Linear Algebra TBD, Probability Theory TBD) 3. CC 2014-2017, Four year 2017-2021
  3. Hi everyone, I applied for masters in applied mathematics (mathematical physics concentration - GR and physical cosmology) for fall 2020 after much consideration but I'm having doubts about whether I'd get into any of these programs. I was wondering if anyone could give me some advice on my chances for these programs and if it's looking pretty bleak, what I should do to better prepare for Fall 2021. Undergrad institution: No reputation Indian university Major: Electronics and Communication engineering GPA: equivalent to B in the USA (first class) Background: International Indian male Relevant math courses: Calculus, differential equations, transforms, numerical techniques, complex analysis and probability. We used Engineering mathematics by B S Grewal, Erwin Kreyszig and Probability by Seymour Lipschutz. GRE general: Quant: 164 (84 percentile) Verbal: 156 (73 percentile) Writing: 3.0 (15 percentile) GRE physics: 770 (62 percentile) TOEFL: R-29, L-30, S-23, W-25 Total: 107 Research experience: (For a total of one year) Did research for a professor at a Indian central govt. research institute. Worked on algorithms in C for adaptive optics (fourier transforms, SVD, correlations) (a co-author acknowledgement in the publication of the work.) Explored the use of image gradients for registration in the context of adaptive optics. Also ended up defining a small technique (A first author paper is in preparation for the same) Technical skills • Programming: IDL, C, MATLAB, JAVA • Software: FFTW, GNU scientific library, MS Office, LATEX • OS: Ubuntu(Debian) and Windows LOR: My supervisor at the central govt. institution, whom I had a great relationship with, wrote me a strong positive letter. My lecturer from my undergrad institute: under whom I completed my curriculum project work. My lecturer from my undergrad institute: who taught us math for 1.5 years. (I know that my background is different. But I have self studied from Apostol calculus. Now I have taken up moocs for real analysis and differential geometry) Schools I applied to (masters in applied mathematics - mathematical physics) UC Davis/ pending UIUC/ pending University of Alberta/ pending University of waterloo/ pending Univerity of toronto/ pending Schools I applied to (masters in physics) UT Austin/ pending Stony Brook university/ pending I am taking up math GRE this october. Should I be applying to MS programs that are ranked lower for next spring (if it's really the case that my chances are not that great.) Thank you so much for your help.
  4. Hi, I am an international student who've gotten admitted to the PhD Program of Applied Mathematics at Waterloo University (funding: 37560 CAD/year). Even though the subject I am currently doing research on (at the 4th semester of my masters) is related to Mechanical Engineering (actually Biomedical Engineering), but the Professor I had an interview with before the admission also works in the same area. Anyway, since I have studied engineering, I don't have any perspective on the future of studying Applied Mathematics at UW. I have applied for the PhD program in Biomedical Engineering at four other Canadian universities (UBC, McGill University, McMaster University, and University of Toronto) and am waiting for their results (I really hope I could get admission to UBC) Currently, I am so stressed out about the results and cannot sleep well at nights. I think I've excessively become obsessed with this matter and couldn't appreciate the admission I have so far. What I am going to ask is that, could anyone provide me with some information about or maybe personal experience of studying at Waterloo University, especially at the mathematics department, and its career opportunities after graduation (which is the most important factor to me)
  5. I currently am graduating with a B.S. in Computational and applied mathematics. I concentrated in statistics and have a minor in it, but am only also a class different from a Statistics B.S. as well. I took a class in mathematics of large data and it concentrated in Laplace and Fourier transformations of data, such as signals within pictures, voice and speaker recognition, and wavelets JPEG. I absolutely loved it. I was wondering what I should do now? I have heard that mathematicians can go to grad school for electrical engineering and not be behind if they are going to focus on signals and processing, which is what I would be doing, but am wondering how feasible it is? I know for a fact that mathematicians transition into systems engineering flawlessly since graduate school of systems engineering is mathematics of processes. However, I know a masters in applied mathematics would also open doors to different worlds, but normally lead to different kinds of jobs than my dream job. Other than that, should I just finish a bachelors degree in electrical engineering? I do not think would be more beneficial but I thought I would ask that as well. any advise would be greatly appreciated Thanks, Tom
  6. I am a 4th year undergraduate mathematics and physics major and I attended a top private liberal arts college. I want to go to grad school for applied math or physics to study nonlinear systems/PDE's but I don't feel ready. I only have one summer of physics research at Caltech-JPL and don't have any graduate level classes. I was wondering if there exist year long research programs to gain experience before grad school...like a post baccalaureate for math or physics?
  7. I'm new to this site so please forgive any breach in protocol. I am currently a math and physics double major at my undergrad institution, which has a small grad program, but I am not particularly interested in attending there. I plan on applying to phd programs in statistics, despite no research in mathematics, although I do have research experience in physics. I also was not able to take any graduate courses because of the double major. I have yet to take my GRE's, though I expect decent scores on general, and I am not sure whether I will take the subject. My gpa is a 3.88, a little higher for math, a little lower for physics. My letters should be really good, although none will come from statistics professors. My question is, is this an issue? Also, what schools would be attainable given the information provided, how many schools to apply to (ie; safety, target, reach). Thank you.
  8. Hello Out of the following, please rank the following applied mathematics programs based on how good they are, their research capacity, and jobs after PhD. A brief explanation for your choices would be priceless. Thanks! 1. University of North Carolina- Charlotte 2. Florida State University 3. Iowa State University 4. University of South Carolina 5. Virginia Tech 6. Washington State University
  9. I am interested in continuing my education in math and I know that I'd eventually like to work on brain-computer interface (theory and application) like mind uploading but was curious if there is a discipline that merges computational neuroscience, biostatistics, AI, and cybersecurity: providing a rigourous curriculum that can be used to pursue these fields. Any input would be greatly appreciated! This is ultimately to maximize my chances of being employed, having a successful career long term. If the opportunity exists, I would equally like to learn more about AI (neural net) and cybersecurity, and I currently enjoy the statistical, predictive modeling (machine learning) work that I do in genetics (similar to data science). I have thoroughly looked through gradcafe, stackexchange, quora, reddit and amassed math topics important in each field. I have highlighted common topics and would like to get you guys' input on the accuracy of this list. MATH TOPICS FOR EACH FIELD cybersecurity - applied number theory (abstract algebra), combinatorics (graph theory), algebraic geometry, information theory, asymptotic analysis, finite fields computational neuroscience - information theory, systems theory (nonlinear dynamics, dynamical systems), evolutionary algorithms (Monte Carlo), state space analysis, signal processing, probability theory AI/ML - neural networks, genetic algorithms, information geometry (Riemannian geometry, information theory, Fisher information), algebraic geometry, manifold geometry, learning theory (Fourier analysis), probability theory, game theory (topology, measure theory), graph theory, Model Free Methods RECOMMENDATIONS Some have recommended biostatistics programs because the curriculum offers a fair amount of 'theoretical' math work. Others, however, have said that biostatistics is a bad choice - sticking to CS or EE would be better. There is always the option to go into pure math but I am concerned about employability of a pure math PhD compared to an applied math PhD. I have played with the idea of work towards becoming a fellow of actuarial science simultaneously instead to gain statistical training - although this would be more oriented towards business, not science There is also the fact that I have a BS in biochemistry. I have done post-bacc work for CS fundamentals, calculus series, diff. eq., linear algebra, statistics, combinatorics, but there is a legitimate chance that I may not have sufficient background for fields (like statistics or applied math) other than biostatistics. I have looked heavily into degrees for applied/computational mathematics, scientific computing (UPENN, Rice, JHU, MIT, Stanford, Maryland) but it seems that these fields are more broadly focused on application reseach for physics, chemistry, biology (like engineering). I've also looked into mathematical biology (aka biomathematics) but it seems not a lot of schools have such a department - it's commonly housed under computational/systems biology. Thank you very much for your time and help!
  10. I am an Applied Math and Bioinformatics double major looking to apply to top-tier PhD programs in Bioinformatics this fall. I was recently offered a data scientist/machine learning role in a large tech company for the summer. I have conducted research in machine learning applications to computational biology for the past two summers, worked in a laboratory for about 2 years, and was recently offered a spot in the Amgen Scholars program at my own university this summer. I want to conduct research in machine learning for biological applications, so this internship is a great opportunity to see the newest innovations in big data research (most of the best research in big data and machine learning is occurring in the tech industry); however, I have heard that many professors do not look favorably on industry internships. Will it hurt my chances of getting into a top-tier PhD program when I apply if I do a pure tech internship (not medically related)?
  11. Also are there a lot of isolation within the department? If I study computational chemistry, for example, I will be talking to chemists, and not to those in finance, civil engineering, computer science in the same department?
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