Grad Students:  Advice for firstyear Ph.D. students (video), by Philip Guo
 101 Tips for Finishing Your Ph.D. Quickly, by ScholarShape
 Own your PhD project: How to take charge of your research, by Niki Kringos
 Tips for developing PhD research questions
 Essential PhD tips: 10 articles all doctoral students should read
 Scientific Writing: Beyond Tips and Tricks, by Judy Swan
 How to write a Great Research Paper, and Get it Accepted by a Good Journal, by Anthony Newman
 How to Write a Great Research Paper, by Simon Jones
 How to Give a Great Research Talk, by Simon Jones
 Skillful writing of an awful research paper
 Designing effective scientific presentations, by Susan McConnell
 40 Useful Words and Phrases for TopNotch Essays
 70 useful sentences for academic writing
 What are the 21stcentury skills every student needs?
 Write good papers, by Daniel Lemire
 PhD Job Facts That No One Told You, by Prof. Leo Rebholz
 The PHD Movie
 OSU Writing Center
 ShareOK
 OSU Latex Thesis Template (thanks to Matt)
Career:Funding: Graduate Fellowship Opportunities: Summer Schools and Postdoctoral Research & Research Centers:Selected TED talks:  Hold your breath for microsculpture, Willard Wigan, 2009
 Be humble  and other lessons from the philosophy of water, Raymond Tang, 2017
 Your elusive creative genius, Elizabeth Gilbert, 2009
 Where good ideas come from, Steven Johnson, 2010
 How we explore unanswered questions in physics, James Beacham, 2016
 The search for planets beyond our solar systems, Sara Seager, 2015
 Get ready for hybrid thinking, Ray Kurzweil, 2014
 How AI can save our humanity, KaiFu Lee, 2018
 Lecture Series:  Mathematical Methods for Engineers I, by Prof. Gilbert Strang, MIT
 Mathematical Methods for Engineers II, by Prof. Gilbert Strang, MIT
 Introduction to Continuum Mechanics, by Prof. Romesh Batra, VT
 Physics I: Classical Mechanics, by Prof. Walter Lewin, MIT
 Physics II: Electricity and Magnetism, by Prof. Walter Lewin, MIT
 Physics III: Vibrations and Waves, by Prof. Walter Lewin, MIT
 Instability and Transition of Fluid Flows, by Prof. Tapan K. Sengupta
 Computational Fluid Dynamics, by Prof. Lorena Barba
 Machine Learning, by Prof. Yaser AbuMostafa, Caltech
 Dynamic Data Assimilation: an introduction by Prof S. Lakshmivarahan
 Introduction to Computer Science and Programming, by Profs. E. Grimson and J. Guttag
 Introduction to Numerical Analysis, by Prof. Tim Kelley
 Probabilistic Systems Analysis and Applied Probability, by John Tsitsiklis
Resources:  I do like CFD & CFD notes, by Hiroaki Nishikawa
 Numerical Fluid Dynamics, by Prof. C.P. Dullemond
 Numerical Fluid Mechanics, by Prof. Pierre Lermusiaux
 Computational Fluid Mechanics, by Prof. Gretar Tryggvason
 Lecture notes on Numerical Linear Algebra, by Joseph E. Flaherty
 Colorful Fluid Dynamics: Behind the Scenes, by Phil Roe
 Turbulence Modeling Resources, NASA LaRC
 Introductory Lectures on Turbulence, by Prof J.M. McDonough
 Fundamentals of Engineering Numerical Analysis, by Prof. Parviz Moin
 CFD Vision 2030 Study: A Path to Revolutionary Computational Aerosciences
 Mathematics Gives You Wings, by Prof. Margot Gerritsen
 Compressive Sensing and Sparse Recovery Lecture, by Prof. Justin Romberg
 Compressed Sensing: Recovery, Algorithms, and Analysis, by Prof. Stanley Osher
 Compressive Sensing, by Prof. Richard Baraniuk
 Reduced order modeling, by Prof. Nathan Kutz
 Compressed Sensing and Dynamic Mode Decomposition, by Prof. Steve Brunton
 Introduction to MPI, by Paul Preney
 HPC Opportunities in Deep Learning, by Greg Diamos Baidu
 Deep Learning For Dummies, by Carey Nachenberg
 CFD in Planetary Science, by Prof. Philip Marcus
 Feynman and Computation, by Prof. Tony Hey
 Quantum computation, by Prof. Michelle Simmons
 Turbulence database from Prof. J. Jimenez
 Python Extension Packages
 Finite Difference Table, by C. Taylor
 Image processing tools
 Latex2PNG
 Compilation Guide
 Advanced High Performance Computing CSCI 580, by Dr. Timothy H. Kaiser
 How do you combine machine learning and physicsbased modeling? by V. Flovik
 The mostly complete chart of Neural Networks, explained by Andrew Tchircoff
 THE NEURAL NETWORK ZOO, by Fjodor van Veen (with links to the original papers)
 Dr. Ali Rahimi's talk at NIPS 2017 on Machine Learning
 Converting from PBS to Slurm
 MPI and OpenMP user guide
 Argonne Training Program on ExtremeScale Computing (2016) or here
 Neural Networks by 3Blue1Brown
 Meet Geoffrey Hinton
 Vivien Mallet: Introduction to data assimilation
 Sophie Ricci: Data assimilation training course
 Stefano Marelli: Metamodels for uncertainty quantification and reliability analysis
 ATPESC 2018 ANL Training
 Essentials of Atmospheric and Oceanic Dynamics, by Prof. Geoffrey K. Vallis
 CM1 by Dr. George H. Bryan
 pyMOR & SIAM J. SCI. COMPUT. 2016 Vol. 38, No. 5, pp. S194–S216
 MoRePaS: Model Reduction for Parametrized Systems
 Max Gunzburger: Uncertainty Quantification for Complex Systems
 Jeremy Oakley: Introduction to Uncertainty Quantification and Gaussian Processes  GPSS 2016
 Uncertainty Quantification Webinar by Dr. Habib Najm
 Fast Quantification of Uncertainty and Robustness with Variational Bayes by Tamara Broderick
 Emily Gorcenski  Polynomial Chaos: A technique for modeling uncertainty
 IPAM/UCLA videos
 Artificial Intelligence, the History and Future, by Chris Bishop
 Chris Fonnesbeck: An introduction to Markov Chain Monte Carlo using PyMC3
 MetropolisHastings, the Gibbs Sampler, and MCMC by Dr. Esarey
 Paul Balzer  IPython and Sympy to Develop a Kalman Filter for Multisensor Data Fusion
