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other experts within the Support for Computational Resources unit at NBIS and related organisations, notably SciLifeLab, National Academic Infrastructure for Supercomputing in Sweden (NAISS), and EuroHPC
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this unique program Duties At the Physics Department of Gothenburg University we are announcing the position as DDLS PhD student in Data driven cell and molecular biology. Data driven cell and molecular
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to the advancement of precision medicine in oncology. A typical workday may involve writing and running code to pre-process sequencing data on a compute server, applying statistical models and algorithms to construct
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National Program for Data-Driven Life Science (DDLS) is a 12-year initiative that focuses on data-driven research, to train and recruit the next generation of life scientists and create strong and globally
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and machine learning to sequences and molecules. This can be a program in bioinformatics, computational biology, machine learning, molecular biotechnology, computational chemistry, molecular physics
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Are you passionate about applying computational approaches to solve problems in biomedicine? We are now looking for an Industrial PhD student in Data-Driven Life Sciences to work on a cutting-edge
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bioinformatics, engineering physics, molecular biology, computer science, or a related field. You should have strong programming skills (e.g., in Python or R) and a keen interest in applying data-driven methods
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located at the Uppsala Biomedical Centre campus. It belongs to the Faculty of Science and Technology and conducts research in biochemistry, organic chemistry, analytical chemistry, and physical chemistry
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interdisciplinary backgrounds and expertise to foster cutting-edge research with high clinical relevance. Project Description Imaging methods such as magnetic resonance imaging (MRI), computed tomography (CT), and
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, engineering physics, biomedicine, or similar Documented skills in data-driven analysis (machine learning using python with TensorFlow, PyTorch, or similar) and computational statistics Specific knowledge of big