"Pursuing the certificate in computational and information science during my Ph.D. empowered me to develop novel research methods and to employ state-of-the-art parallel paradigms in my workflow. Thanks to the excellent training on high-performance computing and the support of PICSciE staff, my research is now at the forefront of what is done in my field." —Noemi Vergopolan, Civil and Environmental EngineeringIntroduction and RationaleComputation is now a crucial tool for discovery in the sciences, engineering, and increasingly so in the humanities. Scientific computation is also a diverse field. It requires a working knowledge of numerical analysis (to develop new and more accurate algorithms), best practices in software engineering (to implement and maintain ever-growing scientific software systems), computer science (to exploit emerging trends in hardware and programming practices), and domain-specific expertise.The graduate certificate in computational science and engineering is only open to Princeton University graduate students who are currently enrolled. It is designed to recognize the achievements of students who have undertaken comprehensive training in these topics, both through formal coursework and through research in their subject area.The certificate program was originally proposed and designed to be part of the Program in Integrative Information, Computer and Application Sciences (PICASso) by Professor J.P. Singh, with the resources required to administer the program now provided by the Princeton Institute for Computational Science and Engineering (PICSciE).In February 2021, the graduate certificate was approved by the Graduate School as a formal credential and will appear in the student's records starting with degrees being conferred in June 2021. With the certificate now officially credentialed, the only significant change to the existing certificate program requirements will be a more formal colloquium each spring at which the program participants will present their research. Each certificate student will be required to present one 20-minute presentation during their program, ostensibly during their final non-DCE year. Certificate RequirementsTo earn the certificate, students must complete four requirements: (1) take for credit and earn a grade of B or better in two core courses; (2) take for credit and earn a grade of B or better in one approved elective course, usually specific to the student’s research area; (3) give a research seminar as part of a colloquium with other program participants at the conclusion of the program; and (4) write a dissertation with a significant computational component, as judged by the dissertation advisor who must write a short letter to certify this requirement. See the FAQ page for additional information.Important: Only one credentialed certificate is allowed per graduate student.RegistrationOnline application is available and is ongoing throughout the year.Core CoursesStudents must take two core courses. This requirement is designed to ensure that all students who earn the certificate have a solid foundation in the basic principles of scientific computing including numerical analysis, software engineering, and computer science. A grade of B or better is required in both core courses. APC 524 / MAE 506 / AST 506 / CSE 524: Software Engineering for Scientific Computing (Fall). The course covers the tools and techniques that are crucial for the effective use of computation in any discipline. Topics include programming in compiled and scripting languages, software management tools and software design, debugging and testing, profiling and optimization, and parallel programming for both shared and distributed memory systems. APC 523 / AST 523 / MAE 507 / CSE 523: Numerical Algorithms for Scientific Computing (Spring). The course covers a broad introduction to numerical algorithms used in scientific computing beginning with a review of the basic principles of numerical analysis including sources of error, stability, and convergence. The theory and implementation of techniques for linear and nonlinear systems of equations and ordinary and partial differential equations are covered in detail. Issues related to the implementation of efficient algorithms on modern high-performance computing systems are discussed. Elective CourseStudents are also required to take one elective course. This requirement is designed to give students expert training in their respective subject areas. Elective courses can be selected from any graduate-level course on campus as long as the course contains a significant computational component. Each elective course must be approved by the Director, through information submitted in the certificate program enrollment application, and the elective course will generally be offered by the student’s home department. Courses dealing exclusively with statistics and/or machine learning cannot be used to satisfy the elective course requirement. A grade of B or better is required in the elective course. Examples of suitable elective courses include but are not limited to: AOS 575: Numerical Prediction of the Atmosphere and OceanARC 574: Computational FabricationAST 559/APC 539: Turbulence and Nonlinear Processes in Fluids and PlasmasAST 560: Computational Methods in Plasma PhysicsCBE 508: Numerical Methods for EngineersCBE 535: Computational Biology of Cell Signaling NetworksCBE 554 / APC 544: Topics in Computational Nonlinear DynamicsCEE 513: Introduction to Finite-Element MethodsCEE 525: Applied Numerical MethodsCEE 532: Advanced Finite-Element MethodsCEE 535/CBE 525: Statistical Mechanics II: MethodsCOS 522/MAT578: Computational ComplexityCOS 551 / MOL 551: Introduction to Genomics & Computational Molecular BiologyCOS 557 / MOL 557: Analysis & Visualization of Large-Scale Genomics Data SetsCOS 597C: Advanced Topics in Computer Science: Theory of Natural AlgorithmsECE 560/PHY 565/MSE 556: Fundamentals of NanophotonicsELE 520: Mathematics of Data ScienceELE 535: Machine Learning and Pattern RecognitionELE 585: Parallel ComputationGEO 422: Data, Models & Uncertainty in the Natural SciencesGEO 441 / APC 441: Computational GeophysicsMAE 501/APC 501/CBE509: Mathematical Methods of Engineering Analysis IMAE 502/APC 506: Mathematical Methods of Engineering Analysis IIMAE 557: Simulation and Modeling of Fluid FlowsMAT 321/APC 321: Numerical MethodsMAT 586/APC 511/MOL 511/QCB 513: Computational Methods in Cryo-Electron MicroscopyMOL 518: Quantitative Methods in Cell and Molecular BiologyMSE 504 / CHM 560 / PHY 512 / CBE 520: Monte Carlo and Molecular Dynamics Simulation in Statistical Physics & Materials Science MSE 512/CHM 511: Phase Transformation in Materials: Theory and SimulationNEU 537/ MOL 537 / PSY 517: Computational Neuroscience & Computing NetworksORF 411: Sequential Division Analytics and Modeling (offered in the past, not offered currently)ORF 522: Linear and Nonlinear OptimizationORF 523: Convex and Conic OptimizationORF 531 / FIN 531: Computational Finance in C++ORF 538: Analytical and Computational Methods of Financial EngineeringORF 544: Stochastic OptimizationSOC 596: Computational Social ScienceThis is not an exhaustive list. Research SeminarThe ability to communicate research to a broad audience, as well as interact with researchers across disciplines on shared tools and challenges, is an important skill for all students to develop. To encourage the development of these skills, students are required to give a research seminar on their dissertation research before graduation, typically in the last year once significant results can be reported. This research seminar occurs as part of a colloquium with other program participants and is organized by PICSciE.The colloquium will occur once per year, typically toward the end of the spring semester. The frequency of the colloquium may be increased to once per semester if needed in a given year if the number of students intending to graduate is large. Students are required to coordinate with the Program Administrator to ensure participation before graduation, and, to help facilitate planning, students are asked to communicate to the Program Administrator any changes to the timeline for completion of degree requirements after submission of the initial online application. Each research seminar is approximately 20 minutes in length with additional time for questions from the audience; the research seminar must be accessible to the broader University community with an interest in computational science and engineering. The University community is invited to participate as audience members in the colloquium. Students enrolled in the program are highly encouraged but not explicitly required to attend the annual (or biannual) colloquium in years when not participating as a presenter. See the Colloquium page for more information. ThesisThe final requirement for the certificate is that the student’s dissertation research must include a significant computational component. Since the role of computation differs across disciplines, the program will rely on the judgment of experts in the specific discipline to certify whether the “significant computational component” requirement has been satisfied. Therefore, the student’s dissertation advisor is asked to write a short letter outlining the role of computation in the dissertation and to certify that the dissertation research has included a “significant computational component” as judged relative to the discipline. In cases where the student’s dissertation advisor does not feel that they can certify the computational component of the dissertation, the advisor can request that a member of the PICSciE Executive Committee or Associated Faculty review the dissertation and submit a letter certifying the computational component of the dissertation. In all cases, the Director will review the certification letter and confirm that this requirement has been met. Note on Overlapping Course Requirements in Home DepartmentIf the student’s home department has a required set of core courses (either specific courses or courses distributed across specifically designated areas), none of these courses may be used to fulfill the certificate elective course requirement. If the student’s home department requires a certain number of courses (either in total or in addition to core course requirements), then no more than two courses used to fulfill the requirements in the home department may be used to fulfill the course requirements of the certificate. In other words, in all cases, students must take at least one additional course beyond the student’s home department requirements. ContactContact Ma. Florevel (Floe) Fusin-Wischusen, PICSciE Institute Manager & Program Administrator609-258-8071 • [email protected]More InformationSee the Graduate Certificate Program FAQ page. Program Director Michael E. Mueller Professor of Mechanical and Aerospace Engineering. Professor of Mechanical and Aerospace Engineering. Associate Chair, Department of Mechanical and Aerospace Engineering. Program Director, Graduate Certificate in Computational Science & Engineering. Participating Faculty A significant fraction of the faculty relies on computation for their research, and all faculty are potential advisers for students in the program. The list of faculty, which includes the PICSciE Executive Committee and Associated Faculty and instructors of elective/key courses, is not exhaustive. Ryan Adams Professor of Computer Science. Director, Program in Statistics and Machine Learning Luc Deike Associate Professor of Mechanical and Aerospace Engineering David August Professor of Computer Science Ian Bourg Assistant Professor, Civil and Environmental Engineering and the High Meadows Institute Ravindra Bhatt Professor of Electrical Engineering Adam Burrows Professor of Astrophysical Sciences. Director Program in Planets and Life Roberto Car Ralph W. *31 Dornte Professor in Chemistry Rene Carmona Paul M. Wythes '55 Professor of Engineering and Finance. Professor of Operations Research and Financial Engineering Jonathan Cohen Eugene Higgins Professor of Psychology. Professor of Psychology and the Princeton Neuroscience Institute. Co-Director Princeton Neuroscience Institute Peter Constantin John von Neumann Professor in Applied and Computational Mathematics. Professor of Mathematics and Applied and Computational Mathematics. Director, Program in Applied and Computational Mathematics Mohamed Abou Donia Associate Professor of Molecular Biology Stephan A. Fueglistaler Professor of Geosciences Stephen Jardin Principal Research Physicist Matthew Kunz Associate Professor of Astrophysical Sciences Simon Levin James S. McDonnell Distinguished University Professor in Ecology and Evolutionary Biology Kai Li Professor of Computer Science Naomi E. Leonard Chair and Edwin S. Wilsey Professor of Mechanical & Aerospace Engineering John Londregan Professor of Politics and International Affairs Meredith Martin Associate Professor of English. Director, Digital Humanities Center Luigi Martinelli Professor of Mechanical and Aerospace Engineering Reed Maxwell Professor of Civil and Environmental Engineering and High Meadows Environmental Institute Michael E. Mueller Professor of Mechanical and Aerospace Engineering. Professor of Mechanical and Aerospace Engineering. Associate Chair, Department of Mechanical and Aerospace Engineering. Program Director, Graduate Certificate in Computational Science & Engineering. Isobel Ojalvo Assistant Professor of Physics Eve Ostriker Lyman Spitzer, Junior Professor of Theoretical Astrophysics. Professor of Astrophysical Sciences. Associate Chair, Department of Astrophysical Sciences. Athanassios Panagiotopoulos Susan Dod Brown Professor of Chemical and Biological Engineering. Chair, Department of Chemical and Biological Engineering. Jonathan W. Pillow Professor of Psychology and the Princeton Neuroscience Institute Frans Pretorius Professor of Physics Eliot Quataert Professor of Astrophysical Sciences Peter Ramadge Gordon Y.S. Wu Professor of Engineering. Professor of Electrical Engineering. Director, Center for Statistics and Machine Learning Laure Resplandy Assistant Professor of Geosciences and the High Meadows Environmental Institute Alejandro Rodriguez Associate Professor of Electrical and Computer Engineering. Director, Program in Material Science and Engineering Clarence Rowley Sin-I Cheng Professor in Engineering Science. Professor of Mechanical and Aerospace Engineering. Olga Russakovsky Assistant Professor of Computer Science Matthew Salganik Professor of Sociology. Director, Center for Information Technology Policy Annabella Selloni David B. Jones Professor of Chemistry H. Sebastian Seung Evnin Professor in Neuroscience. Professor of Computer Science and Neuroscience Mona Singh Associate Professor of Computer Science and the Lewis Sigler Institute for Integrative Genomics Anatoly Spitkovsky Professor of Astrophysical Sciences Brandon Stewart Associate Professor, Sociology John Storey William R. Harman '63 and Mary-Love Harman Professor in Genomics William Tang Principal Research Physicist. Lecturer with the rank of Professor in Astrophysical Sciences Jeroen Tromp Blair Professor of Geology. Professor of Geosciences and Applied and Computational Mathematics. Director, Princeton Institute for Computational Science and Engineering Olga Troyanskaya Professor of Computer Science and the Lewis-Sigler Institute for Integrative Genomics Christopher Tully Professor of Physics Gabriel Vecchi Professor of Geosciences and the High Meadows Environmental Institute. Director, High Meadows Environmental Institute. Deputy Director, Cooperative Institute for Modeling the Earth System Bridgett vonHoldt Associate Professor of Ecology and Evolutionary Biology Michael A. Webb Assistant Professor of Chemical and Biological Engineering David Wentzlaff Associate Professor of Electrical Engineering Claire White Associate Professor of Civil and Environmental Engineering and the Andlinger Center for Energy and the Environment Ned Wingreen Howard A. Prior Professor in the Life Sciences. Professor of Molecular Biology and the Lewis-Sigler Institute for Integrative Genomics. Associate Director, Princeton Center for Theoretical Science. Acting Director, Princeton Center for Theoretical Science Szymon Rusinkiewicz Chair, Department of Computer Science Keushik Sengupta Professor of Electrical and Computer Engineering Robert Tarjan James S. McDonnell Distinguished University Professor of Computer Science Janet Vertesi Associate Professor of Sociology Hakan Türeci Associate Professor of Electrical Engineering