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Science, Computer Science, Applied Mathematics and Statistics, Electrical and Computer Engineering, Biomedical Engineering, or a related field. Experience with a deep learning framework like PyTorch. Strong
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available. In parallel, we prospectively collect skin biopsies from well-phenotyped Parkinson patients (ProPARK cohort). We generate well-defined iPSC. Using advanced genomics and proteomics we aim
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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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process, the role of ISOs passing through molecular clouds, taking part in molecular cloud collapse and disc formation. Your tasks in detail: Perform scientific work on the research topic, in collaboration
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collaboration with leading industrial and academic partners within large-scale Horizon Europe initiatives, where LTU plays a key role in both technical development and scientific coordination. In parallel with
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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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of this grant. In addition, those researchers whose place of residence, at the time of their application, is Tenerife will not be able to benefit either. Selection process The selection process consists of two
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and risk assessment modeling. • Prior experience with CCUS research projects. • Familiarity with high-performance computing (HPC) and parallel computing techniques. Required Knowledge, Skills, and/or
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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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parallel computing techniques including working in the cloud. Preferred Qualifications Education: No additional education beyond what is stated in the Required Qualifications section. Certifications