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study plan. For a doctoral degree, the equivalent of four years of full-time doctoral education is required. The research group Our lab is advancing precision medicine through deep learning models
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and accepted to the PhD program at Stockholm University. Project description Project title: “Deep learning modeling of spatial biology data for expression profile-based drug repurposing”. A new exciting
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with machine learning and generative AI algorithms, with working knowledge of deep learning frameworks such as PyTorch or TensorFlow is considered a strong advantage. • Extensive experience in multi
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managing large amounts of data by designing structured databases (PostgreSQL, MySQL). Machine learning methods such deep learning for analysis of proteomics data and classification of cancer profiles. Since
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the molecular level. While structural predictions using deep learning methods like AlphaFold have revolutionized our understanding of sequence dependent molecular structure, we currently have much more limited
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foundational and applied topics in computer vision and machine learning, with particular strengths in inverse problems, generative models, and geometric deep learning. We work across diverse application areas
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may also include teaching and other departmental duties (no more than 20%). The research will focus on Numerical Analysis for Physics-Aware Deep Kernel Learning This doctoral project lies
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We are offering a WASP, The Wallenberg AI, Autonomous Systems and Software Program, funded PhD position that provides a unique opportunity to develop deep expertise in robotics, machine learning
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spatial proteomics, spatial mass-spec. Experience with single-cell omics is also an advantage. advanced biostatistics and machine learning, such as multivariate analysis, regularization, deep learning
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generative models, AI/ML, polymers, and/or materials science Documented track record of research in the area of the project What you will do Design and implement deep learning (DL) workflows for learning from