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) Application Deadline 15 Mar 2026 - 22:59 (UTC) Country Netherlands Type of Contract Temporary Job Status Not Applicable Hours Per Week 36.0 Is the job funded through the EU Research Framework Programme? Not
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conferences. support the teaching activities at the faculty (up to 10% of the time). What we ask of you A PhD in Machine Learning, Computer Science, Mathematics, Statistics, Physics or a closely related field
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Mathematics (Inverse Problems), Computer Science (Machine Learning, Computer Vision, Efficient Algorithms and High-Performance Computing), and Physics (Image Formation Modelling). Your project is part of
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mechanisms occurring in these materials and their synthesis over all relevant length scales (e.g., cutting-edge ab initio methods, atomistic simulation methods, multi-scale modelling, machine learning) High
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/phd-candidate-in-machine-learni… Requirements Additional Information Website for additional job details https://www.academictransfer.com/357920/ Work Location(s) Number of offers available1Company
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Strong foundation in quantitative data analysis, statistics, and modeling Basic experience with machine learning or AI; ability and motivation to develop advanced skills during the PhD Knowledge
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Description REALISE - Bridging Igneous Petrology and Machine Learning for Science and Society About the REALISE Doctoral Network REALISE will train 15 Doctoral Candidates at the interface of igneous petrology
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of Pisa) and Dr. Stan Van Gisbergen (SCM, Holland) https://www.scm.com/ , who will also serve as industrial mentor. DC9 - Objectives: Apply Machine Learning force fields and sampling methods to model bio
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of machine-learning models capable of analysing the potential of selected antigens as potential vaccine candidate and/or diagnostic target. You will work here The research is embedded within Wageningen
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multimodal data integration across organismal domains and data modalities, making use of state-of-the-art methodologies such as systems/network analysis, artificial intelligence and machine learning and/or