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addressing scientific and technological challenges. The primary technical responsibility of the candidate will be to create and apply generative machine-learning models for the inverse design of nanomaterials
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background in synthetic organic chemistry, although expertise in other relevant fields such as chemical engineering, machine learning, automation, analytical chemistry, and programming (e.g., Python) are also
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enthusiasm. Your experience and profile: We highly value candidates with a background in synthetic organic chemistry, although expertise in other relevant fields such as chemical engineering, machine learning
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to engage in a research initiative focused on addressing scientific and technological challenges. The primary technical responsibility of the candidate will be to create and apply generative machine-learning
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: PhD in one of the following fields, or closely related: machine learning, computer science, applied mathematics, statistics, signal processing, acoustics, bioacoustics Experience in training and
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learning. Requirements Specific Requirements a PhD in a relevant area of machine learning with either a focus on the fundamental aspects of machine learning or experience with healthcare data able
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related field. Proficiency with machine learning methods and corresponding software packages is a plus. Experience with ultrasonic welding is a plus. Fluency in English and proven academic writing skills
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) and extra holidays between Christmas and 1 January; multiple courses to follow from our Teaching and Learning Centre; a complete educational program for PhD students; multiple courses on topics such as
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Apply now The Faculty of Science and the Leiden Institute of Advanced Computer Science (LIACS) are looking for a: Postdoctoral Researcher in Machine Learning (1.5 years, 1.0 FTE), for the Project
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and interdisciplinary team, which consists of enthusiastic PhD students, Post-docs, and industry partners with backgrounds in machine learning, robotics, sensor technology, embedded devices, as