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. The research group is part of the National Program for Data-driven Life Science (DDLS), generously funded by the Knut and Alice Wallenberg Foundation: www.scilifelab.se/data-driven/ Our group focuses on studying
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position is a full-time temporary employment for two years with the possibility to extend by one (1) more year provided project funding is available and the project goes according to plan. The monthly salary
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is carried out in close collaboration with industry and academic partners. Main responsibilities Develop a research plan and design test configurations in collaboration with senior researchers. Perform
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to work well both independently and in a team and have the ability to independently plan and conduct research Proficiency in spoken and written English Documented experience in publishing in international
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programming languages (e.g., Python, R). Experience working in a LINUX/UNIX environment. An excellent molecular biology skillset. Experience with NGS library preparation supported by a strong publication record
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the research on steel recycling and processing. Within the research subject Engineering Materials, there are several research programs spanning broad areas of metallic and ceramic materials research
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communication skills in English are required. Assessment criteria: Good programming skills (e.g., C++, Python, Julia), knowledge of the most common frameworks, e.g., Tensorflow and JAX, and cloud platforms/deployment
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analysis, Python programming, and deep learning frameworks (e.g., TensorFlow, PyTorch) is expected. Prior work in cancer research or medical imaging is an asset. The successful candidate will join an
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society. With unique research expertise, we offer education at the undergraduate and graduate levels, as well as within our international master's programs. The Electronics Materials and Systems Laboratory
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degree in relevant fields (bioinformatics, immunology, computational biology, mathematics, and/or statistics). Strong programming skills in R and/or Python Demonstrated strong ability in analyzing high