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Field
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. Person Specification PhD (or near to completion or equivalent experience) in a relevant field, including statistics, mathematics, computer science, epidemiology. Strong mathematical and quantitative skills
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with strong analytical and numerical skills, and backgrounds in physics, theoretical neuroscience, applied mathematics, computer science, engineering, or related fields. Experience in relevant research
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*) in Bioinformatics, Data-Science or a closely related area such as computer Science, or mathematics * If PhD pending, it must be conferred less than 3 months after closing date. Significant, relevant
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programme designated to attract and empower the world’s brightest early-career researchers. This fellowship supports outstanding scientists who harness Artificial Intelligence (AI) to accelerate breakthroughs
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Computer Science, Mathematics, Physics, Applied Economics, or a related quantitative field. Skills and Knowledge: Knowledge of scientific computing, data assimilation, and machine learning frameworks. Proficiency in
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will need good communication skills, and will be able to work with and disseminate information to both academic and non-academic audiences. You will have a PhD in medical or bio-informatics, epidemiology
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Develop a coherent research program and an emerging research profile in mathematical ecology or mathematical epidemiology. Participate in applications for competitive research funding to support projects
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to the applications of mathematics in cryptography, computing, business, and finance. PAP covers many areas of fundamental and applied physics, including quantum information, condensed matter physics, biophysics, and
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of intelligence, including mathematical and computational models of intelligence, cognitive theories of intelligence, and the neurobiological basis of intelligence. Research and development of new AI or ML
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background in landscape ecology, geography or even landscape architecture is helpful, the work is expected to lean heavily on mathematical, statistical and quantitative analysis of the LiDAR data to not only