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Field
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Sep 2025 - 23:59 (UTC) Type of Contract Temporary Job Status Full-time Offer Starting Date 1 Oct 2025 Is the job funded through the EU Research Framework Programme? Horizon Europe - MSCA Reference
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through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Résultats de traduction disponibles Page
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thermoelectrics. QUALIFICATIONS AND ELIGIBILITY The ideal candidate has a university master’s degree in computational science, physics, or chemistry and is passionate about analytical and numerical modeling and
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linking the farm-level bio-economic model MODAM with macroeconomic Computable General Equilibrium (CGE) modeling approaches. We are offering a temporary part-time position (65% of regular weekly working
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, to characterize immune cell dynamics in murine models of inflammation and cancer. RESPONSIBILITIES: Developing and performing computer simulation of MRI contrast of labelled cells and tissue Labeling and tracking
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degree (or equivalent) in Data Science, Computational Biology, Bioinformatics, Computer Science, Physics or a related field Solid programming skills and knowledge in deep learning, statistical modelling
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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 PhD position in « Development of a Methodology for Designing Hybrid Semantic
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the optimisation strategies to enhance the performance of complex machine learning models such as deep learning model and large language model. Applicants need to have strong background and track records of research
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) Positions PhD Positions Country Austria Application Deadline 30 Sep 2025 - 12:12 (Europe/Berlin) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme
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modeling of complex information systems, and SDU and the Royal Danish Defence College’s established intelligence studies and practice. By introducing computational modeling to traditional intelligence