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excited about building and deploying systems. Work with the PI in mentoring PhD and Master students. Be self-motivated and driven, creative, team-oriented, and able to work efficiently in a
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PhD (or be near completion) in a field such as AI, computer science, signal processing, biomedical engineering, have a strong record of publication in engineering or computer science literature, and
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of the project. Applicants should hold, or be close to completion of, PhD/DPhil in Biology or a related subject. You should have a high level of competence in cell biology and relevant experience demonstrated by
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), to develop systems that improve the efficacy of machine learning-based technologies for healthcare applications. You must hold a PhD (or be near completion) in a field such as AI, computer science, signal
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due to illness, parental leave, clinical service, appointments of trust in trade union organizations, or similar circumstances. Requirements A PhD (or equivalent foreign degree) in a relevant discipline
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scientific productivity with peer-reviewed publications and strong commitment to scientific research. Recipients of recent PhD or MD degree are strongly encouraged to apply. Applicants with experience in
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of results in scientific journals Requirements PhD in Physics, Engineering, Economics, Environmental Sciences, Mathematics, System Sciences or a related field training in formal, quantitative methods
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with partners across Europe: data sharing, code exchange, joint publications and reporting. Your qualities You hold a PhD (or near completion) in Soil Science, Environmental Modelling, Biogeochemistry
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the workpackage team and collaborating with partners across Europe: data sharing, code exchange, joint publications. Your qualities You hold a PhD (or near completion) in statistics, applied mathematics, data
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researchers at Princeton and other institutions, to study novel renewable energy technologies. The candidates are expected to have a PhD degree in Chemical Engineering or related field, and have experience with