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) data. We also analyse macaque electrophysiology data obtained through collaborations. We use machine learning techniques for data analysis and computational modelling with a special interest in
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, statistics or similar. Solid knowledge of machine learning algorithms, statistical modeling, and data analysis techniques. intermediate level in programming languages such as Python (prefered) or R. Good
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, ranging from antibacterial to anti-cancer drugs. To this end, we develop new ways to combine state-of-the-art technologies in metabolomics with mathematical modeling. The candidate will have the opportunity
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, or behavioral data) and be proficient in Python and modern deep-learning frameworks (ideally PyTorch). Experience in computer vision, multimodal data fusion, self-supervised or generative modeling is highly
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chemistry modelling techniques scientific machine learning high-performance computing molecular design, generative AI, database handling and analysis collaborative, project management, presentation and
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development of machine-learning-infused atomistic modeling techniques beyond the state of the art and their application to study important problems in chemistry, physics and materials science. The group has
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dynamical systems), epidemiological modelling, data analysis (statistics, machine learning). • in scientific programming (preferably Python, Matlab, R) Genuine interest in the analysis and modeling
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ADC performance against acute myeloid leukaemia (AML). Laboratory experiments and machine learning models will be implemented to achieve the following aims: Develop a random forest regression model
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PhD Research Fellow in ML-assisted reservoir characterization/modelling for CO2 storage (ref 290702)
strong machine learning and numerical modelling background to add knowledge on the impact of geological heterogeneity and subsurface environments (e.g., depth, exhumation, temperature, pressure) to de-risk
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/Machine Learning engineers. Want to leverage your skills to usher in the era of personalized disease modeling? The Digital Twin Innovation Hub is currently seeking skilled and experienced individuals