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skills, including generalized linear models, multiple machine‑learning algorithms, MOFA and multi‑omics pathway analysis. · Strong background in experimental design, quantitative data analysis, and
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sitting for long periods of time Shift 20 hours per week / hours vary Job Summary This position will support for an artificial intelligence project. Responsibilities include developing algorithms and
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of algorithms, machine learning, optimization, scientific software development and high-performance computing. The division is also an important part of the eSSENCE strategic collaboration on e-science and of
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that includes medical image processing, Artificial Intelligence (AI) algorithm development, and scientific writing. Gain clinical experience including training in radiation oncology software, imaging including
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deep learning models with state-of-the-art algorithms based on histology whole slide images. They may also contribute to research of integration of multimodality data with clinical, radiological images
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evaluation of machine learning, computer vision, and other algorithms, primarily in the context of health. They will be part of the thriving research community of Duke Spark (spark.duke.edu) where AI
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lead the design, statistical optimisation and validation of assays for clinically relevant bladder cancer targets. Their central objective will be to develop an algorithmic workflow to detect new target
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Max Planck Institute for Gravitational Physics, Potsdam-Golm | Potsdam, Brandenburg | Germany | about 7 hours ago
, the LISA Consortium, and the LISA Distributed Data Processing Centre, where the department leads waveform generation and the global-fit deep analysis. Your tasks Research areas Analytical modeling
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devices electrically and statistically — transfer and output characteristics, contact resistance, subthreshold swing, hysteresis, threshold distributions and basic reliability screening
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· Experience with multi-GPU or distributed training is a plus · Ability to work independently as well as part of an interdisciplinary team in a fast-paced environment, while making necessary connections