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programming; Experience programming distributed systems; Experience with parallel and distributed File Systems (e.g., Lustre, GPFS, Ceph) development. Advanced experience with high-performance computing and/or
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. You have experience in matrix algorithms, data compression, parallel computing, optimization of advanced applications on parallel and distributed systems. An excellent scientific track record proven
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willingness to learn: High-performance computing (distributed systems, profiling, performance optimization), Training large AI models (PyTorch/JAX/TensorFlow, parallelization, mixed precision), Data analysis
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programming; Experience programming distributed systems; Experience with parallel and distributed File Systems (e.g., Lustre, GPFS, Ceph) development. Advanced experience with high-performance computing and/or
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and/or distributed systems techniques. • Proficiency in programming languages such as Python, C++, or similar, as well as experience with HPC environments and parallel computing. • Demonstrated hands
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distributed intelligence across the computing continuum. In this role, you will have the opportunity to lead and contribute to cutting-edge research aimed at transforming scientific data management and
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Experimental Sciences or equivalent training programs; - PhD Degree in Chemistry; - Training in DFT and CASSCF computational methods and molecular dynamics studies; - Experience in physicochemical and structural
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areas. Qualifications To be eligible for a postdoc position, you must have a PhD in Computer Science, Automation, Electronics, Mechatronics, Industrial IT, or another relevant subject area. The PhD should
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, Industrial Computing, Communication, and Control Laboratory), an advanced test environment for future industrial systems and cyber-physical environments. The goal is to develop robust, distributed, and
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FieldMathematicsYears of Research ExperienceNone Additional Information Eligibility criteria Academic: PhD in applied mathematics, computer science, or medical physics. Scientific interests: applied mathematics