17 Mathematics "http:" PhD positions at University of Twente (UT)

PhD position (f/m/d): Large-scale impact of wind farms on atmospheric flow

dynamics, mechanical engineering, computational physics, applied physics, mathematics, geophysics, or related subject areas. Experience with programming languages such as Fortran, C/C++, MATLAB, or Python is

PhD position (f/m/d): Assessing the interplay between wind farms and clouds

engineering, computational physics, applied physics, mathematics, geophysics, or related subject areas. Experience with programming languages such as Fortran, C/C++, MATLAB, or Python is advantageous

PhD position on “Exploring transport limitations in alkaline electrolysis”

CAE-C (CPE). Website for additional job details https://www.academictransfer.com/342256/ Work Location(s) Number of offers available1Company/InstituteUniversiteit

PhD position (f/m/d): Pioneering simulations of offshore wind farm turbulence

in fluid dynamics, mechanical engineering, computational physics, applied physics, mathematics, geophysics, or related subject areas. Proficiency in programming languages such as Fortran, C/C++, MATLAB

PhD position on Fast and Accurate Integral Equation Methods for Computational Problems in Wave Phenomena

-edge research at the intersection of computational mathematics and its applications in physics, engineering, and material sciences, with a specific focus on addressing direct and inverse problems in

PhD position on Cardiorespiratory Modelling and Simulation in Critical Care

candidate who is driven by curiosity and has: -or will shortly acquire-, a Master degree, or equivalent, in Technical Medicine, Biomedical Engineering, (applied) Mathematics, Computer Science or a related

PhD position Reinforcement learning for digital finance

: Good programming skills. Experience with machine learning libraries (e.g., TensorFlow, PyTorch, Jax) is helpful; Strong mathematical background, in particular statistics & probability, linear algebra

PhD position on Calibration in Deep Learning for Zero Downtime in Cyber-Physical Systems

on calibration in deep learning at the Pervasive Systems Research group, Department of Computer Science, Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) at the University of Twente in

PhD position on Sparse Training for Energy-Efficient Deep Learning

efficiency of deep neural networks. Investigate the mathematical underpinnings of sparsity in deep learning and its effects on learning dynamics, and generalization. Implement and benchmark sparse training

PhD position on Sparse Training for Deep Reinforcement Learning

original research on sparse-to-sparse training techniques, exploring new frontiers in algorithmic development for DRL. Investigate the mathematical underpinnings of sparsity in deep reinforcement learning