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Field
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Science. Commitment to undergraduate and graduate education. Demonstrated expertise in machine learning/deep learning and software development (Python; PyTorch/TensorFlow). Peer-reviewed publications and strong
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lab’s website https://sites.duke.edu/corinnelinardiclab/ . Be You Work Performed · Perform literature reviews to guide research · Design and execution of standard in vitro assays ongoing in the lab
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integrating biomedical, epidemiological, or environmental data. Must show solid skills in computational modeling, multivariate statistics, and/or machine learning. Proven proficiency in the English language
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machine learning, deep learning, or computer vision Experience with Python and common AI frameworks (PyTorch, TensorFlow) Interest in hallucination detection, robustness, trustworthiness, and (optionally
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-FNR PEARL Research Grant in the area of Information Systems Engineering, and, depending on interest, in fields, such as Generative AI & Machine Learning, Data Privacy, Cyber Security, Digital Identities
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being responsible for the confocal microscope (maintenance). Resources provided (equipment, IT, etc.): office equipped with a computer workstation, equipped laboratory bench, reagents and equipment shared
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within the ANITI HUCAD project which aims to develop Artificial Intelligence (AI) systems fostering human-machine collaboration for effective deliberations. It aims to enhance the argumentation
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, etc.), and data-driven methods (optimisation, generative AI, agent-based modelling, machine learning). Our work provides decision support for policy makers, industry stakeholders, and researchers by
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, MONAI) Strong interest in image analysis / computer vision and pattern recognition, including but not limited to biomedical applications Strong interest in applied machine learning, including but not
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knowledge of machine learning (e.g., in the areas of object detection and identification, generative AI, etc.) Good written and spoken English skills (min. level B2) Good written and spoken German skills (min