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Field
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immunology is an advantage. Experience in high-performance parallel computing is an advantage. Experience with machine learning and or other mathematical approaches used in (bulk and single-cell) immune
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become a core member of a team working on electrical machines, electromagnetic design, magnetic and insulation materials, thermal management, control, construction and testing of high-performance
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: neuromorphic algorithms, machine learning, classifier development, AI programming Key tasks include experimental and/or computational research, collaboration within the project team, publishing results in high
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Computer Science. This is a trainee position that will give promising researchers an opportunity for academic development through a PhD education leading to a doctoral degree. The hired candidate will be
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the project, not exceeding the maximum period set by FCT for such grants. RENEWALL, in case of the project extension Renewable is subject to performance if the candidate is enrolled in a: MSc program
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mechanisms for continuous monitoring of the performance of the models and their pedagogical impact. Prepare high-level scientific and technical reports, systematizing the methodologies, architecture and
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-scale knowledge graphs, graph and semantic embedding techniques, and/or use of high-performance computing resources in research will contribute to the strength of your application. Required Qualifications
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guaranteed access to the university’s high-performance supercomputer BlueBEAR. Additionally, the successful candidate will have the opportunity to supervise students, acquire teaching experience, participate
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performance computing clusters would also be advantageous Strong foundation in Fluid Dynamics Strong prior experience in CFD – particularly in battery fire combustion and spread. Strong skills in turbulence
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become a core member of a team working on electrical machines, electromagnetic design, magnetic and insulation materials, thermal management, control, construction and testing of high-performance