17 machine-learning-phd PhD positions at Radboud University in Netherlands

PhD Position in Computational Biology: Using Machine Learning to Understand the Immune System

computer vision? Would you like to apply AI and machine learning for fundamental research in biology? Then you have a part to play as a PhD candidate. By combining simulations and machine learning, you will

PhD Position in Computational Biology: Using Machine Learning to Understand the Immune System

in biology? Then you have a part to play as a PhD candidate. By combining simulations and machine learning, you will help us develop new, innovative methods to extract knowledge from immune cell

PhD Candidate: Generative Diffusion Modelling and Associative Memory at the Donders Centre for Cognition

main responsibility will be to work on research projects in generative machine learning. These projects require both training of deep neural networks on large datasets and performing theoretical analyses

PhD Candidate: Computational Cognitive Neuroscience at the Predictive Brain Lab

of artificial intelligence and machine learning have put artificial neural networks firmly on the map as a promising approach to both model and understand biological brains. This PhD project aims to harness

PhD Candidate: Generative Diffusion Modelling and Associative Memory at the Donders Centre for Cognition

projects in generative machine learning. These projects require both training of deep neural networks on large datasets and performing theoretical analyses and calculations to elucidate their properties. In

PhD Candidate: Computational Cognitive Neuroscience at the Predictive Brain Lab

2024 Apply now The last decade has witnessed a paradigm shift in how we view perception and cognition. Brains are increasingly thought of as prediction machines. Come and join us as a PhD candidate to

PhD Candidate: Integrating Biopsychological Data to Capture Individual Differences at the Donders Centre for Cognition

have experience in quantitative analysis of cognitive performance data. You have a demonstrable affinity with using mathematical models and/or machine learning methods. You are experienced at programming

PhD Candidate: Experimental Neuromorphic Computing Leveraging Stochasticity

physics and materials sciences, artificial intelligence, computational and high performance computing, and computer hardware and software engineering. Together we aim to develop parallel Markov-chain Monte

PhD Candidate: Integrating Biopsychological Data to Capture Individual Differences at the Donders Centre for Cognition

Science or a related field. You have experience in quantitative analysis of cognitive performance data. You have a demonstrable affinity with using mathematical models and/or machine learning methods. You are

PhD Candidate: Visual Perception and Decision-Making

of visual decision-making, sensory uncertainty, and decision confidence. Research methods include computational modelling, brain imaging (fMRI, MEG), machine learning, behavioural methods, and other