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Networks. The project encompasses several challenges in the gene regulatory network (GRN) field, from simulating realistic networks and data to accurate inference of GRNs from noisy gene expression data
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chemistry, materials chemistry, inorganic and structural chemistry and organic chemistry. The research projects are many from theory to experiment, from basic research to more applied projects often focusing
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mathematician (doctoral student). Karlsson’s group is part of the Division of Optimization and Systems Theory within the Department of Mathematics at KTH. Currently, a large focus of the group is to develop
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academia and industry. Requirements The following qualifications are required: Solid knowledge in mathematics and statistics, in areas such as linear algebra, probability theory, machine learning, high
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in computer science, engineering, data sciences, applied mathematics, machine learning, or another related field; or Have completed at least 240 credits in higher education, with at least 60 credits at
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KTH Royal Institute of Technology, School of Electrical Engineering and Computer Science Project description Third-cycle subject: Computer Science This project involves generative modeling
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, probability theory, etc) A competence in quantitative topics equivalent to a mathematics, statistics, physics, computer science, or engineering degree is required (if your degree was not in one of these domains
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). Interpretation of results using theoretical concepts from evo-devo theory. Qualification requirements Researchers are appointed primarily for purposes of research and must hold a Swedish doctoral degree or
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an international environment and is focused on animal biology. Outstanding and high impact research is conducted in broad fields, from genomics to ecosystems, nerve cells to behavior and evolution to conservation
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experts in the field of protein engineering, protein production, affinity ligand design and characterization, and machine learning for protein design. This unique PhD position is a 4-year collaborative