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spatial mass spectrometry. Experience with single-cell omics is also an advantage. Advanced biostatistics and machine learning, such as multivariate analysis, regularization, deep learning, or network
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interdisciplinary approach encourages contributions to related projects, including applications of machine learning to autoimmune disease and non-invasive diagnostics using cell-free nucleic acids. Duties Develop and
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experience of application of artificial intelligence including machine learning and deep learning algorithms. Documented programming skills in Python, R, or MATLAB. Very good knowledge of English, spoken and
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with our research team, you will contribute to projects involving data integration, advanced analytics, and machine learning. While the projects are primarily computational, they are closely connected
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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
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and documented background in machine learning, deep learning, data analysis and programming. Previous experience in research and knowledge in bioinformatics, biophysics, biochemistry, molecular biology
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, the following are also required: Documented experience of application of artificial intelligence including machine learning and deep learning algorithms. Documented programming skills in Python, R, or MATLAB
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Engineering and Autonomous Systems division . We offer advanced PhD courses where we extend the fundamentals in optimal control, machine learning, probability theory and similar. The research and learning
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We are looking for a highly motivated, skilled, and persistent PhD student with experience in computational fluid dynamics (CFD) and some knowledge in structural analysis. The research aims
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of robotics, electromobility and autonomous driving. We offer advanced PhD courses where we extend the fundamentals in optimal control, machine learning, probability theory and similar. The research and