190 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" positions in Sweden
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/or spatial genomics, computational biology, machine learning, bioinformatics, and systems neuroscience. Prior experience with deep learning applied to biological data is a plus. Practical experience
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) processing, robotic applications (hardware/software), excellent programming skills (including lower-level languages, such as “C”), and experience in neural networks / machine learning. After the qualification
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with catalysis/photochemistry Programming skills using Python and MATLAB Analysis of complex scientific data through machine learning What you will do Plan experiments together with your supervisor and
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Machines, (IMOL), Poland, and the Leicester Institute of Structural and Chemical Biology, United Kingdom. Your work may include clinical and biomedical projects. It may also include technique development
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Machines, (IMOL), Poland, and the Leicester Institute of Structural and Chemical Biology, United Kingdom. Your work may include clinical and biomedical projects. It may also include technique development
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manufacturing. It is meritorious to have previous experience in data analysis and processing with Python (or similar), preferably including documented experience with machine learning tools. It is meritorious
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advanced level (higher education) in the research subject or equivalent competence. Experience with deep learning and machine learning tooling.· In-depth knowledge of LLMs and Transformer architectures
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that support the unit for area protection and marine spatial planning, as well as operations at SLU Aqua. Your profile You have documented expertise in marine ecology and computer vision and machine learning
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well as the programmes in statistics, cognitive science and innovative programming. Read more at https://liu.se/ida The position is based at the Division of Statistics and Machine Learning (STIMA). We conduct research
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located at SciLifeLab in Stockholm. Our research is focused on cell biology, spatial proteiomics and machine learning for bioimage analysis. The aim is to understand how human proteins are distributed in