21 Statistics positions at Eindhoven University of Technology in the-netherlands

PhD in Statistics

that the Department of Mathematics and Computer Science of the Eindhoven University of Technology is opening a PhD position in Statistics. We are looking for a motivated and enthusiastic candidate with a background in

2 PhD's on digital twins for modelling and forecasting induced seismicity

will focus on: Modelling the statistics of induced seismicity. Modelling the spatial distribution of seismicity. Benzi, R., Kumar, P., Toschi, F., & Trampert, J. (2016). Earthquake statistics and plastic

2 PhD positions with a focus on Accelerating Rarefied Gas Dynamics

work in a consortium consisting of university groups with complementary skills in fluid dynamics and statistical physics (Fluids and Flows, TU/e) and machine-learning techniques (AMLab, UvA), and

PhD on human-centered AI and attention in cognitive technologies

experimental research, including knowledge of and demonstrable experience with applying (state-of-the-art) statistical techniques. Experience with data wrangling (e.g., in R or Phyton). Open-minded and motivated

PhD position on Green Hydrogen Supply Chains

statistics). Excellent coding skills (e.g., in Java, Python, Julia, MATLAB). A research-oriented attitude. Ability to be self-propelling and drive your own research. Ability to work in an interdisciplinary

PhD Learning Analytics-based dashboards for supporting students blended learning

-design and a thorough statistical evaluation in field experiments. We will consider, among others, educational theories that focus on planning activities, such as goal-setting theory, feedback theories

PhD in Probabilistic Machine Learning

/continual learning with evolving data Job requirements Master’s degree in Mathematics, Statistics, Computer Science, or a related field Excellent analytical and mathematical skills Affinity with developing

PhD on computational modeling of reverberation chambers

of reverberation chambers. This is why most modeling for reverberation chambers is rooted in stochastics and statistics, yet the disadvantage of such an approach is that the underlying assumptions are only weakly

PhD on Revenue Management for Complex Stochastic Systems

. Markov decision theory and dynamic programming) and applied probability (Bayesian statistics). Excellent coding skills (e.g., in Java, Python, Julia, MATLAB). A research-oriented attitude. Ability to be

PhD on computational modeling of reverberation chambers

why most modeling for reverberation chambers is rooted in stochastics and statistics, yet the disadvantage of such an approach is that the underlying assumptions are only weakly underpinned by a