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Field
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collation, mixed precision, multi-GPU; experiment tracking (W&B or MLflow), configuration management (Hydra), strict seed and artefact reproducibility. Graph machine learning. PyTorch Geometric or DGL
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, administration, and strategic evolution of the groups high-performance computing (HPC) infrastructure supporting cutting-edge AI, computer vision, and multimodal learning research. The successful candidate will
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31.07.2026, Academic staff We are seeking a researcher in Scientific Machine Learning (SciML) to join the project "Data science at scale" at the Technical University of Munich, Germany. Ideal
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Faculty.Instructor.Adjunct Electrical and Computer Engineering - Pennsylvania-Pittsburgh - (26005016) Qualifications: Ph.D. in Electrical Engineering with expertise in electrical power systems ECE
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Faculty.Instructor.Adjunct Electrical and Computer Engineering - Pennsylvania-Pittsburgh - (26005055) Qualifications: Ph.D. in Electrical Engineering with expertise in electrical power systems ECE
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25.08.2026 Application deadline : 20.09.2026 The Cluster of Excellence "Machine Learning - New Perspectives for Science" together with the Tübingen AI Center at the University of Tübingen offers a
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initiation latency, movement speed, gait characteristics, postural control, motor variability, and other behavioural descriptors. ESSENTIAL REQUIREMENT PhD in machine learning, artificial intelligence
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architectures and embedded platforms (ARM Cortex-M, NPU, FPGA, embedded GPU), e.g., via academic courses and/or project courses Research experience (e.g., through a Master thesis work or research internships) is
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into robust, maintainable analysis tools and pipelines Implement and optimize large-scale deep learning workflows on GPU-enabled High-Performance Computing (HPC) environments Prototype using emerging computer
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. Position Overview The successful candidate will develop and apply advanced computational and machine learning methods to large-scale genomic, clinical, and imaging datasets, working across one or more of the