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opportunity for an enthusiastic and motivated postdoctoral fellow in data-sciences and biomedical informatics to work on exciting human and veterinary health studies, such as the identification of novel
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, or computational. The Experimental Petrology group at RSES is a world-leader in high pressure experimental petrology and the application of cutting-edge microanalysis to experimental products. Our strategic research
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@seas.harvard.edu . Applications will be reviewed on a rolling basis. Basic Qualifications A Ph.D. in Mathematics, Computer Science, or a related field, by the start of the appointment. Additional Qualifications
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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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recognition in the field. Job Requirements PhD in Computer Science, Mathematics, or a related discipline. At least two years postdoctoral experience. Extensive publication record at leading cryptography and
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. robotics, computer science, electrical/electronic engineering, etc. • Extensive experience in robotic motion planning and control, especially in obstacle avoidance and contact-aware task execution with
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in Computer Science, Mathematics, or a related field. Strong publication record in leading cryptography and theoretical computer science conferences. Demonstrated ability to conduct independent
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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
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, applied mathematics, statistics, computer science, strong gravity, condensed matter theory, particle physics, quantum fields & strings, quantum gravity, quantum foundations, quantum Appl Deadline: 2026/01
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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