868 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" positions in Sweden
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Field
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perform 3D single-particle tracking and establish pipelines to characterise the particle motion using a combination of established tracking algorithms and machine-learning-based approaches. Additionally
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experience) of their research career and must not have been awarded a doctoral degree. Where to apply Website https://umu.varbi.com/en/what:job/jobID:907734/ Requirements Research FieldBiological
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. The department has approximately 160 staff members, of which 30 are PhD students. For more information, visit https://www.umu.se/en/department-of-ecology-and-environmental-science/
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dimensions andanalyse particle trajectories using a combination of established tracking algorithms and machine-learning-based approaches. You will further correlate the diffusive behaviour of viruses
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education to enable regions to expand quickly and sustainably. In fact, the future is made here. Description of work You will be working in the laboratory of Marta Bally (https://ballylab.com/ ), in close
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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
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universities, as well as a key centre of intellectual talent and innovation. We are Sweden’s largest technical research and learning institution and home to students, researchers and faculty from around the
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: October 2026 Full call details, eligibility criteria, application templates, and a matchmaking platform for identifying potential supervisors are available at: https://www.scilifelab.se/data-driven/ddls
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. The application should be registered via Umeå University’s e-recruitment system Varbi (https://umustipendie.varbi.com/en/what:job/jobID:887298/ ) and submitted by the deadline 18 March 2026. Please apply at with
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computational methodologies, ranging from atomistic and electronic-structure–based materials modeling and characterization, via machine-learning and high-throughput methods, to ab initio calculation