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systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and algorithms. Our research integrates expertise from machine learning, optimization
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algorithms. Our research integrates expertise from machine learning, optimization, control theory, and applied mathematics, spanning diverse application domains such as medicine, energy systems, biomedical
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higher education credits (ECTS). Relevant courses include, for example, image processing, computer vision, machine learning, deep learning and neural networks, as well as courses in Python, GPU programming
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. In addition, the following are requirements for the role: Strong programming and quantitative skills, particularly in Python and/or R. Experience in deep learning, machine learning, or large-scale
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modeling of protein dynamics We are seeking a highly motivated PhD student to join a DDLS-funded project at the interface of structural proteomics, protein biophysics, and machine learning. The position is
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Join MultiD Analyses AB and the University of Gothenburg to develop innovative bioinformatics and machine learning methods for RNA Fragmentomics, with the ambition to improve cancer care through
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multi-omics integration with advanced machine learning, including artificial neural networks, to predict disease-relevant splice variants across cardiometabolic diseases. By leveraging extensive meta
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candidates to be interested to learn these practical skills. While the project has and initial plan with funding from the Swedish Research Council (see below), the different parts of the project will be