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Description of the workplace The postdoctoral researcher will join the Protein Evolution research group, led by Gemma C. Atkinson, at the Department of Experimental Medical Science, Lund University
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Research Group at Karolinska Institutet investigates how the human central nervous system develops, how these programs are disrupted by injury and disease, and how they can be harnessed for regeneration and
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samples, lack of training data and sample variability. In this project we aim to develop AI/ML workflows for improved quantitative analysis of LNPs. Your responsibilities will include optimisation of data
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postdoctoral researcher with a solid background in one or more of the following areas: game theory, optimization algorithms, and numerical methods. The successful candidate will develop efficient algorithms and
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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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develop algorithms for this purpose. The group collaborates with several national and international research groups, edits one of the major journals on data privacy (Transactions on Data Privacy), and has
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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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orchestration across different network components, as well as to the development of sensing algorithms and ISAC solutions. The postdoctoral researcher will also play an active role in coordinating research
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algorithms for fluid-structure interaction solvers What you will do Independently develop numerical methods and codes for fluid-structure interaction of wind-powered ships Carry out and analyse high-fidelity
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international collaborators. The group's interests cover a wide range of areas including extremal and probabilistic combinatorics, combinatorial optimization, graph theory, game theory, algorithmics and geometry