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studies independently, working with diverse datasets, developing algorithms and decision rules, and contributing to the refinement of data-driven intervention strategies. Tasks As a postdoctoral researcher
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on the resulting algorithms and pipelines. As an emerging paradigm, differentiable programming builds upon several areas of computer science and applied mathematics, including automatic differentiation, graphical
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qualities You hold either PhD in deep learning techniques and an interest in climate science, or a PhD in Meteorology or Climate Science having clear experience with deep learning techniques. You possess
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contribution to marine conservation strategies. You will join a small but diverse and multidisciplinary team of research assistants, PhD candidates, residents (specialists-in-training), veterinarians
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Bachelor's and Master's students, 550 employees and 150 PhD candidates. Our educational and research programmes are closely connected with UT research institutes Mesa+ Institute, TechMed Center and Digital
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background and interests. Candidate Profile We are looking for candidates who meet the following criteria: PhD in a related discipline. Expertise in one of the following areas: Single-cell and spatial
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software Writing reports and research articles where you will be co-author. Your qualities You hold a PhD (or are close to submission, or have recently submitted) in statistics, data science, or a related
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to involve the postdoctoral researcher in the supervision of a PhD-candidate, and we encourage and facilitate publishing and attracting research funding beyond the involvement in PERSIST. In short, we try to
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profile, experience and research proposal. Planning and autonomy: The objective is to study the state of the art of planning algorithms that would support onboard autonomous operations of a rover system on
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scientists, Research Fellows and PhDs in a vibrant research environment at UNU-MERIT and at partner organizations – UCL (Jack Stilgoe), CWTS at Leiden (Rodrigo Costas), Ingenio at CSIC-UPV (Ismael Rafols), and