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Field
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well as experience with HPC environments and parallel computing. Demonstrated hands-on experience and understanding of developing scientific data management, workflows and resource management problems. Strong problem
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University. Our portfolio covers fields from natural sciences to engineering and information sciences. In parallel with basic research, we develop ideas and technologies further into innovations and services
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results. Machine Learning skills to automise comparison process. Unbiased approach to different theoretical models. Experience in HPC system usage and parallel/distributed computing. Knowledge in GPU-based
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hydrodynamics and/or N-body simulations in the star and planet formation context Experience in the field with HPC system usage and parallel/distributed computing Knowledge in GPU-based programming would be
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developing or applying parallel algorithms and scalable workflows for HPC resources. Experience developing or applying privacy-enhancing technologies such as federated learning, differential privacy, and
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and phenotype. Targeted Quantification of Bioactives: Developing and validating highly sensitive targeted quantitative assays (e.g., using Multiple Reaction Monitoring, MRM, or Parallel Reaction
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parallel/multiplexed assays, etc.) is desirable. Ability to interpret and discuss experiments and critically contribute to writing of manuscripts and grant proposals is expected. Well-organized, able
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, Mixture-of-Experts; distributed training/inference (e.g. FSDP, DeepSpeed, Megatron-LM, tensor/sequence parallelism); scalable evaluation pipelines for reasoning and agents. Federated & Collaborative
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platform enables us to test hundreds of different conditions in parallel and assess their impacts on human immune responses, such as antibody production. We routinely work with industry partners to exploit
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of individual Milky Way-like galaxies Programming in Python, C/C++ and/or Fortran, and experience in parallel code development Experience in the development and use of tools for analysis of output of hydrodynamic