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dependent predictive deep learning models, and physical mechanistic models (thermodynamic and kinetic models etc.). Examples of suitable backgrounds: machine learning, programming, mathematics, physics. You
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using Cell Painting and high-content imaging. Deep learning and multivariate methods, both supervised and unsupervised. Development of software and pipelines for analysis of large-scale image data
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an Assistant Professor is to develop research skills as an independent researcher and acquire scientific and pedagogical qualifications. The position has a focus on research but may also include
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Assistant Professor is to develop research skills as an independent researcher and acquire scientific and pedagogical qualifications. The position has a focus on research but may also include teaching and
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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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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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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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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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implementing AI/ML methods (e.g., machine learning, deep learning) for life science research. Collaborating with research groups to identify needs and opportunities for AI/ML support in their projects
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will find yourself in a team that values creativity and allows you to influence the decisions made within the group. Furthermore, we value continuous learning and encourage you to allocate time for