20 machine-learning-"https:" "https:" "https:" "UCL" Postdoctoral positions at Uppsala universitet
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you interested in working with machine learning for batteries, with
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and free-energy calculations in explicit solvent. The postdoctoral researcher will employ machine-learning-accelerated methods throughout the workflow, contribute to the development of new computational
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HCI and cybersecurity, to cancer research tools and methods for numerical analysis and machine learning. The research work takes place in a multidisciplinary team with a focus on image processing with
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integration of AI-based vision and active machine learning to optimize the efficiency of the process. Writing publications and present research results from the project on conferences. Collaboration with
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to apply Website https://uu.varbi.com/en/what:job/jobID:891842/type:job/where:39/apply:1 Requirements Research FieldChemistryEducation LevelPhD or equivalent Research FieldChemistryYears of Research
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, and doctoral students active on both campuses. Learn more about the Department of Archaeology, Ancient History, and Conservation here: Department of Archaeology, Ancient History and Conservation
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funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you interested in developing new image analysis and machine learning methods
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(https://www.globischlab.org/research-projects/). The analysis will be included into our EU-network PANCAID (https://pancaid-project.eu) that will lead to interdisciplinary scientific interactions within
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good spoken and written English is required. The applicant should be capable of working both independently and as part of a team, with problem-solving skills and an openness to learning new methods
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by: Assistant Professor Chenyu Wen, telephone +46 762275768, chenyu.wen@angstrom.uu.se . Information about the Division of Solid-State Electronics can be found at https://www.elektroteknik.uu.se