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, or representation learning. Experience analysing large-scale single-cell omics data. Experience with integrative multi-omics data, such as genomics, proteomics, or metabolomics. Experience with relevant machine
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) to help shape and accelerate the adoption of advanced machine learning and AI in data-driven Life Science research. At the SciLifeLab Bioinformatics Platform (NBIS), a unique national infrastructure with
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agents Experience developing infrastructure for machine learning workflows Experience contributing to open data platforms or large scientific databases Awareness of diversity and equal opportunity issues
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quality standards and contributing as part of a collaborative infrastructure team. Information about the division/project Chalmers Mass Spectrometry Infrastructure (CMSI) is part of the Division
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. Required qualifications: PhD in a field such as physics, systems biology, applied mathematics, machine learning, or related fields. Strong programming skills (e.g. Python) and experience with modern ML
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infrastructures that supports large-scale data and hypothesis-driven research in the field of molecular biosciences. SciLifeLab (www.scilifelab.se ) operates nationally, engaging all major Universities of Sweden
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on development of novel computational methods with state-of-the-art machine learning for gaining fundamental insights into healthy and diseased human tissues of the heart, cardiovascular system, and
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. You demonstrate an interest in and ability to learn and apply new methods and ways of working. You show a high level of integrity, motivation, and flexibility in your work. Further information
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societal challenges. Our department is an exciting workplace with research in a broad technology-related area, from basic research to large-scale applied research, and with close contact with students
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measurements. Have a background in computational biology, bioinformatics, or machine learning for biological problems. Have experience with modern deep learning frameworks (PyTorch, JAX, or equivalent). Have