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science. We are looking for a candidate with a PhD in either engineering/computer science/physics/mathematics. Experience with ML implementation (ideally interpretable ML and/or generative AI) is required
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of forests under climate change. The PhD student will work in the Forest Remote Sensing group at the Department of Forest Resource Management at SLU, collaborating closely with other engineers and scientists
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Master Programmes, at the Faculty of Medicine, and at the Disciplinary Domain of Science and Technology. The department has a yearly turnover of around SEK 500 million, out of which more than half is made
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Admission to Doctoral (PhD) Studies in the subject Engineering Sciences with specialization in Biomedical Engineering at the Division of Biomedical Engineering, Department of Materials Science and
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includes image data processing/analysis and writing project reports. Qualification requirements Required Qualifications PhD in molecular biology or equivalent competence. Experience working in a laboratory
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-cell imaging and analysis will be used to investigate cell and cluster morphology. The scientific interests and background of the PhD student will be a major factor in the design of the project. A person
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of new techniques for mass spectrometry imaging and single cell mass spectrometry to reveal chemical processes of importance to biological function and dysfunction. The research group has recently received
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engineering, thermal engineering, or a related field with a strong focus on fluid dynamics, energy systems, heat transfer processes, multiphase flows, or similar areas. A deep understanding of the physics and
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-rich sequences. These intricate structures are thought to function as critical protein-binding sites, influencing essential processes such as transcription, replication, telomere stability, and DNA
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these processes using large-scale population genomic data from modern-day and prehistoric humans. The PhD position is part of the The SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS