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of MSI advances our understanding of complex brain processes. The prospective PhD candidate collects brain MSI data and develops novel machine learning methods in connection to generative models such as
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particularly valuable. Documented experience with machine learning and biostatistics is also highly meritorious.You can find information about education at postgraduate level, eligibility requirements and
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Physics (with focus on machine learning and bone microscopy analysis, Soft Matter Lab) The Department of Physics at the University of Gothenburg is located in the center of Gothenburg, with approximately
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. Qualifications Required: PhD. Applicants who have obtained a PhD degree or achieved the equivalent competence in seven years or less prior to the end of the application period will be given priority. Research
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than 40 PhD students and postdocs. Research at the DSAI ranges from foundational methods in machine learning (e.g., optimization, bandits and reinforcement learning) to application domains in biophysics
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at the single-cell level, using tools from optimal transport, mathematical optimization, and machine learning. In addition to method development, the work includes applying and benchmarking algorithms on both
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. The project explores the role of tumor-promoting inflammation in cancer progression through bioinformatics-driven, machine-learning and multi-omics analyses integrated with experimental data. Ideal candidates
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includes participating in research projects and third cycle courses. The work duties will also include teaching and other departmental duties (no more than 20%). Your research focus will be machine learning
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) biological knowledge about GRNs from bioinformatics and system biology, (b) graph theory and topological data analysis for network modeling from mathematics, and (c) robust machine learning (ML) and GenAI from
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highly recognized research. More information about us, please visit: The Department of Biochemistry and Biophysics . Project description The successful candidate will develop machine learning (ML