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through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description In the Faculty IV: School of Science and
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, Statistical Physics, Genome Annotation, and/or related fields Practical experience with High Performance Computing Systems as well as parallel/distributed programming Very good command of written and spoken
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strong background in applied mathematics Excellent programming skills (Python, C/C++) Good experience in machine learning and parallel computing Good organisational skills and ability to work both
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timetable for the four-year project to be submitted to DAAD. Development of relevant analytical methods and setting up of required laboratory equipment will be conducted in parallel. Execution of the research
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GPU-capable, parallelized simulation frameworks. Work closely with experts in HPC and power systems to enhance scalability and computational performance. Disseminate your findings through scientific
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, including parallel file systems. Uses of tools, scripts or programming, the automation of routine tasks are required to reduce manual workload, improve response time and to ensure system reliability. Creates
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to enable massively parallel processing of ABMs on NVIDIA graphics processing units (GPUs), without the need for specialist understanding of GPU programming or optimisation. This project will explore
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) experience in code development with parallel programming techniques using the message passing interface (MPI) library Proficiency in writing code with C, C++ and/or Python Ability to demonstrate strong written
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of the developed process will be explored through parallel screening and the selectivity of the catalysts refined through subsequent rounds of catalyst design. The successful candidate will work within the
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) Country Italy Type of Contract To be defined Job Status Full-time Hours Per Week To be defined Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related