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target and mechanism of action of the lead compound; ▪ To prepare experimental reports, presentations, figures, and chemistry sections of scientific publications; ▪ To support a PhD student. Where to apply
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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
the theoretical foundations of data science and AI. Responsibilities: Conduct research on automated reasoning and proof checker, AI-assisted collaboration. Develop and analyze algorithms for learning and
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associate will be conducting research on topics in machine learning and computational materials science.. In compliance with NYC’s Pay Transparency Act, the annual base salary range for this position is
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sends e-mail) ) Applications are considered on a rolling basis. Does this position pay above the required minimum?: Yes. The expected base pay range for this position is listed in Pay Range field. The pay
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Employment 1.0 FTE Gross monthly salary € 3,706 - € 5,760 Required background PhD Organizational unit Faculty of Science Application deadline 15 October 2026 Apply now Contribute to breakthrough
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classification and multi-layered environment mapping - Digital twin generation for natural environments - Semantic scene-understanding in natural environments for robust decision-making - Learning-based
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the opportunity for three weeks of training in higher education teaching and learning. The job also includes opportunities for teaching on basic and advanced level. participation in supervision of master and PhD
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processing, machine learning, computational imaging, and clinical translation. Beyond your individual research contributions, you will serve as a technical coach for the PhD researchers, helping to align
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infrastructures. You will contribute to research projects enabling secure, interoperable, and scalable use of clinical data for AI and machine learning applications in complex diseases such as Cancer, Alzheimer's
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for more details https://www.pepr-diadem.fr/projet/ai-mahc-2/ ). The Postdoc will work in tandem with a PhD student and will benefit from the PEPR DIADEM infrastructure, including advanced platforms, as