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implementing, optimizing, or integrating quantum libraries such as Itensor, CUDA-Q, Qiskit, or PennyLane. Experience debugging and profiling distributed-memory parallel applications. Knowledge of Git and modern
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. Knowledge of systems programming skills and concepts Experience with fundamental OS and storage concepts. Experience with programming heterogenous architecture. Preferred Qualifications: Experience with CUDA
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. Experience implementing, optimizing, or integrating quantum libraries such as Itensor, CUDA-Q, Qiskit, or PennyLane. Experience debugging and profiling distributed-memory parallel applications. Knowledge
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in advancing the clinical and commercial translation of a cutting-edge multimodal endoscopic platform. As part of the Label-free Bioimaging Laboratory, the successful candidate will contribute high
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questions in the areas of self-supervised/label-efficient learning and explainability of deep neural networks (XAI) are being developed, particularly for use in biomedical applications. Further information
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imaging and spectroscopy. Experience with data analysis or the ability to perform basic biochemical work with proteins and DNA, e.g., fluorescence labelling, enzymatic reactions will be highly rated in
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to the clinic The post holder will be based in the Department of Biomedical Computing as part of the School of Biomedical Engineering & Imaging Sciences, King’s College London, a vibrant community of engineers
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++, Rust, or similar languages. CUDA experience is a plus. Passion for interdisciplinary research in an innovative and collaborative environment. Application Process: Submit your CV, cover letter, and
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-molecule TIRF microscopy, biochemical reconstitution, and fluorescent labeling, we will watch individual RNA molecules and degradosome complexes at work, capturing millisecond-scale dynamics that shape gene
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computer architecture Parallel programming of HPC/AI accelerators (CUDA, OpenMP, SYCL, etc.) Salary Gross annual: €39,224 Application Deadline 07 October 2025, 12:00 (CET) via University of Trento