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regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods, statistical analysis and efficient algorithm and data structures (https
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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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KTH Royal Institute of Technology, School of Engineering Sciences Job description The AICell Lab (https://aicell.io ) in the department of Applied Physics at KTH and Science for Life Laboratory is a
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or senior staff scientist. More information: https://www.scilifelab.se/researchers/simon-koplev/ Qualifications Requirements A doctoral degree or an equivalent foreign degree. This eligibility requirement
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students, master’s and project students as well as communication of research results through scientific articles in well-established scientific journals and presentations at international conferences