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in large pre-trained models (vision-language models), generative models (flow matching, diffusion), simulation-based inference, and robust and active learning. The group has a wide network of
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. Simulation-based inference (SBI) addresses this by training neural networks, such as flow-matching generative models, on simulated events. The project aims to develop efficient, robust and calibrated SBI
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model of the human cell. The program is led by Jan Ellenberg, Director of SciLifeLab and Mathias Ulhen, Director of the Human Protein Atlas, together with a collaborative, multi-institutional
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prediction, most current models still describe proteins largely as static structures and do not fully capture the conformational ensembles that underlie protein function. This PhD project aims to address
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, longitudinal patient and population registries and biobanks. Project description Large language models (LLMs) enable the extraction of clinical information from unstructured medical text. However, current LLM
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Join ABC Labs and KTH as an Industrial PhD Student to build data-driven models of human biology with multimodal health data — interdisciplinary impact, real-world healthcare. About the role We
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School of Electrical Engineering and Computer Science at KTH Project description Third-cycle subject: Electrical Engineering The department of Decision and Control Systems (DCS) is currently seeking
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described. The project has three main objectives: (1) Use simulation models to make inferences on the role of sex ratio selection on sex chromosome evolution in a different meiotic drive scenarios, (2
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epidemiology, statistics, bioinformatics, and cancer biology. We have both “dry lab” and “wet lab” components. Currently the group consists of 1 associate senior lecturer, 1 postdoctoral researcher, 1
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including epidemiology, statistics, bioinformatics, and cancer biology. We have both “dry lab” and “wet lab” components. Currently the group consists of 2 postdoctoral researchers, 1 statistician (part-time