11 statistics positions at Delft University of Technology (TU Delft) in PhD

PhD Position Multivariate Dependence Modelling and Statistical Machine Learning Algorithms for Patient Risk Profiling

://www.tudelft.nl/ewi/over-de-faculteit/afdelingen/applied-mathema… ) is offering a full-time PhD position in the area of Multivariate dependence modelling and statistical machine learning algorithms for patient

PhD Position Rheumatic Digital Twin | Integrating Clinical and Omics Data

. Requirements Specific Requirements You hold a MSc degree in bioinformatics, computer sciences, statistics, life sciences or a similar area. You possess a strong background in data analytics and machine learning

PhD Position Unraveling Cloud Patterns in the Climate System

weather statistics. During your PhD research, you will explore concepts from complex systems theory and data-driven approaches to multiscale systems to unravel the mesoscale cloud patterns that keep us from

PhD Position Theoretical Biophysics

regulation and development on the one, and macroscopic stimuli (light, touch) on the other hand. We use tools from statistical physics, information theory and non-linear dynamics to understand the how well a

PhD position Distributed Sensor Fusion for Swarms

fields of automotive, satellites, robotics and many more. There are various challenges in such large-scale distributed networks i.e., the low-cost sensing, decentralized statistical inference, distributed

PhD Position Optimal Exploration of Networks

theory and statistics. You thrive on conducting research geared to real-world application in the security domain and are intrinsically motivated to collaborate with the Netherlands Police. You harness your

PhD position in Large Language Models for Knowledge Harvesting, Sharing, and Management

statistics and qualitative methods (e.g., content analysis) and understanding of user-centred design methods. Ability to work in a team, elicit project requirements, take initiative, obtain results, be

PhD Position Machine Learning on Graphs

Science, Artificial Intelligence, Electrical Engineering, Applied Mathematics, or any field related to the research topic; A strong mathematical background in optimisation, statistical learning, linear

PhD Position Developing a New Modelling Framework to Identify Air Pollution Sources in Urban Area

best represent this variability in outcome with a statistical model and take its inverse? Is such framework adaptive and generalizable to changes in urban setting? Do you want to improve and develop

PhD position in Large Language Models for Knowledge Harvesting, Sharing, and Management

statistics and qualitative methods (e.g., content analysis) and understanding of user-centred design methods. Ability to work in a team, elicit project requirements, take initiative, obtain results, be