896 machine-learning-"https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" "UCL" "UCL" "UCL" positions in Sweden
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network modelling and machine learning for regulatory inference. - Functional validation of candidate TE‑CREs in spruce using UPSC transformation and somatic embryogenesis pipelines; evaluating drought
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description Description of work You will be working in the laboratory of Marta Bally ( https://ballylab.com/ ) at the Department of Clinical Microbiology, at Umeå University ( https:// www.umu.se/en/department
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programs for both Swedish and international students. Read more at https://www.biology.lu.se/ . Find more reasons why Lund University and the Faculty of Science are right for you here and here , and learn
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, machine learning, etc. Building a quantum computer requires a multi-disciplinary effort involving experimental and theoretical physicists, electrical and microwave engineers, computer scientists, software
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an innovative spirit, in close collaboration with wider society. Chalmers was founded in 1829 and has the same motto today as it did then: Avancez – forward. Where to apply Website https://academicpositions.com
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teaching environment at the department. The main language of the PhD program is English. However, non-Swedish speaking students are expected to acquire basic skills in Swedish during the period of employment
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Initiatives in Forest Research (WIFORCE) program. The successful applicant will work on the development of bioacoustic monitoring methods using automated recording units (ARUs), deep learning methods, and
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solutions across the natural sciences. Your workplace You will be employed at the Department of Mathematics in the Division of Applied Mathematics, https://liu.se/en/organisation/liu/mai/tima . The research
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addition to conventional software, the scope includes engineering of AI enabled systems (primarily ML and LLM), and thus MLOps (Machine Learning Operations), datacentric AI, and legal and ethical aspects of AI
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projects in data-driven nutrition, such as: statistical modelling, AI, and machine learning on large epidemiological cohorts, diet and health data analysis of omics data (metabolomics, proteomics, microbiome