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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Tremblay en France, le de France | France | about 2 months ago
on advancing the understanding of lanthanide and actinide materials and developing synchrotron-based methods for selective rare-earth recovery from nuclear and industrial waste in collaboration with six European
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aims to understand the metabolic and neural mechanisms of food choice and specifically how modern, ultra-processed foods influence these systems. Lab website: https://fbri.vtc.vt.edu/research/labs
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Strong background in biomechanics, biomedical engineering, computational mechanics, or equivalent fields. Strong foundation in numerical methods, especially the finite element method. Proficient in python
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collaborations to implement cosmological analyses derived from the observation of Type Ia Supernovae. This work, carried out within the framework of the ANR SCINF project, aims to develop inference methods based
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structure methods, quantum Monte Carlo, tensor networks, or quantum embedding methods, etc. - ML-augmented numerical method development. - High-performance computing (HPC
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establish a research profile. Develop and execute innovative research projects. Develop, train, and evaluate modern machine-learning models on GPU/HPC infrastructure. Integrate AI methods with scientific
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, including appropriate controls, statistical approaches, and methods to ensure reproducibility and scientific rigor. · Independently interpret experimental results, troubleshoot technical and
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technology or system of higher education, in Portugal or abroad. 6.2 — The score obtained in the curricular evaluation method is expressed on a numeric scale of 0 to 20, considering the valuation up to two
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Our preferred method of application is online via our website. Please click ‘apply’ below or go to https://www.imperial.ac.uk/job-applicants/ and search using reference number ENG03959 Application
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Geophysics, Physics, Earth Sciences or related field obtained within the last 7 years; demonstrated experience in numerical geophysical modeling or computational mineral physics; proficiency in at least one