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the national Data-Driven Life Science (DDLS) program. About the position and the project As an industrial PhD student, you will be employed by the startup company PredictMe AB while being formally enrolled as a
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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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experienced researchers and have access to high-performance computing, university servers, as well as a rich national network of neuroscience expertise through SciLifeLab and the DDLS Research School. We
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processing, computer vision, machine learning, deep learning and neural networks, as well as courses in python, GPU programming, mathematical modeling and statistics, or equivalent. The University may permit
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university. More information about us, please visit: the Department of Biochemistry and Biophysics . Project description Project title: Perturbation-based Multi-omics Inference of Gene Regulatory Networks
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-driven analysis. The PhD student will be part of the DDLS Research School, a national program offering courses, workshops, and networking across Sweden. The project is conducted in collaboration with KTH
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will be affiliated with the national DDLS program, through which you will have access to computing resources, the national DDLS research school, and other training and networking opportunities throughout
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. Experience in deep learning, computer vision, or neural network development. Experience with live-cell microscopy, fluorescence microscopy, or analysis of 3D/4D image data. Experience in cell biological
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for the PLP Strategic Area. Key responsibilities may include: Contributing to the overall scientific direction and strategic development of the PLP program, including developing a long-term vision from
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to improve the interpretation and matching of mass spectrometry data, a field in which Sweden holds a leading global position. To this end, the doctoral student will use and develop computational tools, and a