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of complex brain processes. The prospective PhD candidate collects brain MSI data and develops novel machine learning methods in connection to generative models such as flow matching. Therefore, the doctoral
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at Sahlgrenska Academy of relevance include genomics, metagenomics, culturomics, proteomics, transcriptomics, software development, machine learning, and other statistical analyses of large-scale health data
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: https://www.slu.se/institutioner/vaxtbiologi-skogsgenetik/ Read more about our benefits and what it is like to work at SLU: https://www.slu.se/om-slu/jobba-pa-slu/ PhD Student: DDLS integrative
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on innovative development and application of novel data-driven methods relying on machine learning, artificial intelligence, or other computational techniques. The specific focus is on development and
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focus on innovative development and application of novel data-driven methods relying on machine learning, artificial intelligence, or other computational techniques. The applicant is expected to develop
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, the following are required: – Documented several years of experience in training, evaluating, and deploying machine learning models, including deep neural networks and relevant frameworks – Documented several
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candidate, who is eager to learn and has a genuine scientific interest. Extensive knowledge in and practical experience with protein expression and structural characterization is mandatory. Documented
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: The primary location will be at the KI Flemingsberg campus, but since the project is a collaboration with the SciLifeLab DDD platform some parts of the project will also be performed in Solna. https
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community of Digital Research Engineers. The offices also host computer infrastructure and machine learning/data science/research data management experts, who develop, build, and manage the local and national
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aspects of both. The first direction concerns the data-driven discovery of dynamical rules underlying developmental trajectories. The aim is to develop and analyze quantitative frameworks that learn