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record-keeping, and ability to manage multiple parallel experiments. -Demonstrated independence in research and problem-solving. -Track record of peer-reviewed publications. -Effective communication skills
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world leader in fertilizer production, is a major starter client for the University providing capital and research funds. In parallel, a new portfolio of clients is growing with the development of an R&D
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(HPC/parallel environments), and open/reproducible release of data and analysis scripts under FAIR principles. Dissemination through high-impact journal publications and conference presentations in solar
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. Qualifications: Familiarity with machine learning interatomic potentials, CPU and GPU parallelization, knowledge of LAMMPS and molecular dynamics, experience with first principles calculations of dielectric and
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organizational skills, meticulous record-keeping, and ability to manage multiple parallel experiments. -Demonstrated independence in research and problem-solving. -Track record of peer-reviewed publications
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skills in general and a taste for meticulousness are essential. In parallel, interest for soft matter concepts and modelling will be of help to interpret the data. Experience in data analysis (including
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algorithms will be assessed for neurodegeneration mapping in Alzheimer’s disease brain organoids. In parallel, the technology and algorithms will be applied to fish health research, supporting studies on ulcer
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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | about 2 months ago
are neutral? Which rare variants impact in enhancers’ activity? and What is the penetrance of that impact? To address these questions, massive parallel reporter assays (MPRAs) have been developed to test in
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in AI to study natural and artificial minds in parallel, creating the opportunity to make discoveries about ourselves and to find new ways to understand and improve AI systems. Appointments will be
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learning frameworks (e.g. PyTorch, TensorFlow) and relevant libraries. Practical experience inscalable data processing, including the use of parallel computing, cloud platforms,and distributed systems