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skills; preference will be given to candidates with experience in writing scientific papers and projects. 9.3) Experience in experimental method optimisation and laboratory-based research for marine
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computational mechanics, applied mathematics, physics, computer science, biomedical engineering or a related field Good knowledge of numerical methods and finite-element analysis Solid programming skills in C
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periods, they must constantly understand their surroundings to make smart decisions and complete tasks, such as moving safely without collisions or handling objects. Recent methods for robotic situational
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CIIMAR - Interdisciplinary Center of Marine and Environmental Research - Uporto | Portugal | about 1 month ago
to level 33: gross monthly salary of €2 408,11 (two thousand four hundred and eight euros and eleven cents); with added allowances for food, holiday and Christmas paid separately. Selection Methods: Ranking
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CIIMAR - Interdisciplinary Center of Marine and Environmental Research - Uporto | Portugal | about 1 month ago
apart. Selection methods: A global appreciation of the candidates’ merit and motivation (valued from 1 to 10) will be made based on the evaluation of their scientific and curricular track-record, in
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methods, e.g. Monte Carlo, Latin Hypercube sampling, to quantify uncertaintyIdentify influential parameters to support robust monitoring designUse two well-monitored landslides as benchmarksDevelop OED
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Epidemiology is a research department at Aarhus University Hospital, within the Department of Clinical Medicine at Aarhus University. Researchers in the department use advanced epidemiological methods to study
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at the time of application: Applications must be formalized by sending the following documents: i) Detailed Curriculum Vitae; ii) Documents proving the academic degrees obtained and their classification* (in
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ML frameworks like PyTorch/JAX Genuine interest in MLFFs, simulation methods, and foundational ML research Desired skills: Experience with atomistic simulation codes: ASE, FHI-aims, VASP, CP2K
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and evaluation of methods that leverage multimodal signals to improve the performance of multilingual models for low-resource languages, such as Luxembourgish. Particular emphasis will be placed