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a doctoral degree in one of the relevant fields (e.g., Plant Genetics and Breeding, Plant Biology, Genomics, Evolutionary Biology), or currently be pursuing the degree to be received by January 1
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the day-to-day operations of the Institute for Genomics and Evolutionary Medicine (iGEM). Under general supervision, completes administrative tasks, such as management of faculty calendars and contacts
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Non-Tenure-Track Assistant Professor of Research - Genetic Variation and Evolution (IGEM) - (26001700) Description Position Summary The Institute for Genomics and Evolutionary Medicine (iGEM
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demonstrations. The successful candidate will work at the intersection of multi-disciplinary modelling, advanced AI algorithms, and decision-support tool development. Responsibilities will include programming
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 2 months ago
(PETs) and privacy assessment functionality based on MAGNET scientific advances By default all developed software will be open-source. Tasks may include developing algorithms, e.g., cryptographic
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, Algorithm Design. Competencies, Skills and Knowledge Essential Fluent in English, both written and verbal. Able to operate within Heriot Watt University Malaysia and liaise closely with other campuses
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. Develop motion-planning, task-planning, perception, control, and feedback algorithms for operation in complex laboratory environments. Integrate robotic manipulators with cameras, force/torque sensors
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specialties including but not limited to quantum algorithms, quantum error correction, quantum computing architectures, quantum information, and quantum simulation of physical systems. Successful candidates
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with expertise in quantum computing, theory and algorithms, or cybersecurity. UNM CS has 21 tenured and tenure-track faculty, including nine NSF CAREER Award recipients and one PECASE recipient. Two
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Develop algorithms for reconstruction of virtual histopathology images from sparse phase-contrast CT acquisitions of oncological specimens Comparison with standard histology and assessment of algorithm