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publications and contribution to collaborative proposals. Support of graduate student mentorship and lab coordination. Required Qualifications & Experience PhD in Materials Chemistry, Extractive Metallurgy
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Qualifications: We seek exceptionally strong candidates with a PhD in statistics, biostatistics, computer science or a related field. Candidates with demonstrated accomplishment in academic research, as can be
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: 256443 Minimum Education and Experience: This position requires a PhD (or other doctoral degree) in education, public policy, social work or related field. In addition, it requires: Strong data analysis
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complete the PhD by the start date of the fellowship. The names and email addresses of three referees, who will be contacted automatically by the online application system with an invitation to upload
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robots are therefore required. One of the goals of this project is to commercialise. You must have a strong computer science background and have experience in one or more of the following areas: Computer
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Information Theory. While excellent candidates with other research interests might be considered, priority will be given to those able to relate to one or more of the above topics. Applicants must have a PhD in
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1 fte - 1 fte Stay up to date with new vacancies! Want to be the first to know about vacancies that match your interests? Let us know what you're looking for, and we'll send you an email as soon as a
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becomes essential. This project will focus on building a comprehensive digital twin of a future quantum computer to investigate how classical subsystems scale and interact, and how this scaling impacts
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following areas: Computer Vision, Robotics, Evolutionary Computation, Deep Reinforcement Learning, and Machine Learning. This should include a proven publication track record. You should also have: Research
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. Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online. Applicants must have (or be close to obtaining) a PhD. Appointment at Research