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Materials (CQM) group led by Prof. Jose Lado and work under the supervision of RCF Fellow Dr. Adolfo O. Fumega. Requirements We seek a highly motivated student with: A Master’s degree in physics, chemistry or
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information about the position please contact: Prof. Denis SCUTO Your profile Master's degree in Digital History, Data Science, Historical Migration Studies, Digital Humanities, or a related discipline Proven
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systems”, coordinated by Prof. Dr. Marco Salvalaglio and Prof. Dr. Axel Voigt and funded by the German Research Foundation (DFG). The core activities will focus on the investigation of disordered correlated
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in working with large data sets and the development of numerical models. Basic knowledge of glaciology or geodesy. Good expertise in programming, e.g. in Python, MATLAB, or other high-level programming
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interest in environmental health and Exposome research; expertise in programming and quantitative data analysis, including machine learning in R/Python; affinity with bioinformatics; strong collaboration
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. The studentship will commence from September 2025 onwards, under the supervision of Dr Rebecca Baggaley and Dr Johan H Thygesen (IHI, UCL), Dr Rachel Burns (Institute of Epidemiology and Health Care, UCL) and Prof
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of Wageningen University and Research. You will be supervised by Dr Imme Benedict and Prof. Jordi Vila Gureau de Arrelano (chair group holder). Your qualities You are/have: A successfully completed – or soon
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relevant Master's degree (or exceptional Bachelor's) in biomedical/mechanical engineering, materials science, or computer science, with experience in mechanical design/textiles and programming (Python/MATLAB
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ID: PMP_TRR408_C5 Investigators: Prof. Dr. Allister Loder, TUM Professorship of Mobility Policy, and co-supervised by at least one leading international researcher Requirements
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forms from land via inland waters to sea. You will synthesise, test, and use the reported methane kinetics from labs and culture experiments to construct the model using Python programming language. You