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information about us, please visit: www.dbb.su.se . Project description The candidate will develop machine learning (ML) strategies, primarily revolving around interpretable ML and generative AI, to study
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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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data. Much focus is on large scale analysis based on machine learning, deep learning/AI, as well as handling and analyzing large 3D microscopy data. You will work with shorter and longer projects and
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Extensive knowledge of relevant machine learning and AI techniques Self-motivated individual with ability to work independently Teaching and mentorship abilities or interests in personal development A
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innovative development and application of novel data-driven methods relying on machine learning, artificial intelligence, or other computational techniques. More specifically, at NRM this research will be
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various versions of ProQ. The group comprises 5 PhD students, one postdoc, and one senior researcher. Qualification requirements Requirements are: Doctoral degree including work in machine learning applied
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in multimodal imaging. Experience in machine learning is highly valued. You will support user-driven research projects and develop integrated data workflows spanning light microscopy (confocal, super
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registries and biobanks. The applicant is expected to have a strong computational focus on innovative development and application of novel data-driven methods relying on machine learning, artificial
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in artificial intelligence (AI) to join our growing biomedical innovation team. In this pivotal role, you will lead and contribute to the design, development, and deployment of machine learning
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been awarded a PhD or a qualification from a foreign higher education institution deemed equivalent to a Swedish PhD. The applicant must also have demonstrated technological and methodological expertise