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in Python programming. Experience with machine learning methods, bioinformatics, and data science. Familiarity with generative AI tools for protein design and protein language models. Knowledge
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northern Sweden create enormous opportunities and complex challenges. For Umeå University, conducting research about – and in the middle of – a society in transition is key. We also take pride in delivering
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methods, including modern machine learning methods, to draw inferences from register data. A third project “Integrative machine and deep learning models for predictive analysis in complex disease areas“ is
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successfully conducting research as well as postgraduate and undergraduate education within areas such as autonomous systems, complex networks, data-driven modeling, learning control, optimization, and sensor
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systems, complex networks, data-driven modeling, machine learning, optimization, and sensor fusion. The division has extensive collaborations both with industry and other research groups around the
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northern Sweden create enormous opportunities and complex challenges. For Umeå University, conducting research about – and in the middle of – a society in transition is key. We also take pride in delivering
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university. More information about us, please visit: the Department of Biochemistry and Biophysics . Project description Project title: Biology-informed Robust AI Methods for Inferring Complex Gene Regulatory
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or predictive modelling of pathogen biology or host-microbe systems for which multidimensional, genome-scale experimental data are now available or it may use population-scale genetic, clinical, or public health
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. You enjoy combining experimental laboratory work with theoretical analysis and modelling. While your main focus will be the research project and your own development as a researcher, the position also
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methods in applied mathematics and computational modeling, this specific project aims to uncover new insights into how blood cells form in both healthy and disease states. A key objective is to model