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with Unity or XR development, deep learning frameworks (e.g., PyTorch, TensorFlow), or real-time sensor data processing is considered a strong merit. Prior experience in reinforcement learning
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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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one or more of the following areas: Single-cell and spatial transcriptomic methods Scientific programming in Python and/or R Machine learning or deep learning frameworks (e.g., PyTorch, TensorFlow
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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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Description of the workplace Automatic Control is an exciting and broad subject, covering both deep mathematics and hands-on engineering. Historically it has been instrumental in many areas, from
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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 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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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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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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of Communications Engineering at the Department of Electrical and Information Technology. The division has 8 senior researchers and around 20 PhD students, and a deep collaboration with industry. The division works