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Field
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training machine learning models (ideally with a focus on LLM), high-performance computing, data management, and software architecture Strong Python programming skills and familiarity with machine learning
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, Bash). Experience working in a Unix/Linux environment, including setting up and managing High Performance Computing (HPC) clusters. Familiarity with metagenomic data analysis and machine learning
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terrestrial networks, non-terrestrial network entanglement distribution. Your profile PhD degree in wireless communications, signal processing, machine/deep learning or a closely related field in Electrical and
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teaching and student supervision activities in areas related to your expertise. What we ask of you Your experience and profile A PhD degree in AI (e.g., machine learning, natural language processing
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-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data driven models for complex data, including temporal data
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Qualification requirements PhD or equivalent academic qualifications with a specialization in computational musicology, computer/data science, informatics, sound and music computing, or other related field
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and oral formats Author peer-reviewed publications, and Work effectively in a large, multidisciplinary team of engineers and chemists . Basic Qualifications Must be a recent PhD graduate within the last
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. Strong skills in geospatial analysis. Strong skills in image analysis and machine learning. Proficiency in scientific programming and data analysis using tools such as Python, R, MATLAB, or similar
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 3 months ago
PhD in computer science, mathematics, physics, bio-/medical informatics or related fields, specializing in image analysis or machine learning, proficiency in deep learning techniques (CNN, VIT
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computational physics, computational materials, and machine learning and artificial intelligence, using the DOE’s leadership class computing facilities. This position will utilize methods such as finite elements