956 computational-physics-"https:"-"https:"-"https:"-"https:"-"L2CM" positions at Nature Careers
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photonics, nonlinear optics, and frequency metrology is highly desirable. Specific skills of interest include design of integrated photonics devices using commercial computational electromagnetic modeling
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Faculty Position — Research Scientist in Cardiology, Cardiac Regeneration and Translational Cardiova
an exceptional research scientist to establish a cutting-edge program addressing fundamental challenges in cardiovascular disease through innovative approaches in regenerative medicine, cardio-oncology, or related
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) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission of teaching and
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and services by utilizing the computerized scheduling system in an accurate, efficient manner. Maintains scheduling (clinic-specific) information and computer knowledge to ensure safe and effective
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) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission of teaching and
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computational modeling, in vivo biological assays, and radiation physics and engineering approaches to define the mechanisms and optimal radiation dosimetric parameters by which FLASH-RT mitigates radiation
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research, internships, or employment. Willingness to be trained and learn new techniques. Strong organizational skills, ability to follow instructions carefully, and attention to detail. Physical
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on the status of projects and work in progress. Proven ability to work within time constraints to achieve experimental results. Strong time management skills. Physical Requirements Remaining in a normal seated or
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integrating clinical big data and artificial intelligence, the program aims to identify novel therapeutic targets and accelerate the translation of fundamental discoveries into personalized medical solutions
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, and train deep learning models on the resulting data to design new antibiotic compounds that evade both current and likely future resistance mechanisms. Your computational work will directly steer