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Developing computational models and running computer simulations in science and engineering still requires substantial expert knowledge. Agentic artificial intelligence (Al) offers a great
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field. The successful candidate must possess expertise in distributed AI/ML systems and computer networks. Good knowledge and practical skills in distributed AI/ML, networked systems, data management, and
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present scientific results. # Software and tools - Proficiency in standard computer tools. - Experience with mass spectrometry data processing and analysis software. # Personal skills - Autonomy, rigor, and
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Program Description Overview The IAS School of Mathematics welcomes applications from mathematicians and theoretical computer scientists at all career levels, and mid-career scientists (5-15 years
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computer science, data science, statistics, bioinformatics, electrical engineering, computer engineering, biomedical engineering, mechanical engineering, operations research, robotics, computational neuroscience
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and biophysics, good computer programming skills, and working knowledge of UNIX, phyton, and shell scripting is highly desired. Experience in molecular simulation softwares and analysis tools such as
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Computer Science, Robotics, Systems Engineering, Electrical and Computer Engineering, Mechanical Engineering, Chemical Engineering, Materials Science & Engineering, Chemistry, or a related quantitative scientific
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Computer/Presentation skills Ability to make decisions and meet deadlines Ability to work on one’s own initiative as well as in a team environment Qualifications – (Essential): A PhD in neuroscience
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models) to extract and compare outcomes reported across clinical trial registries, protocols and publications. Working with computer scientists, statisticians, trial methodologists, outcomes researchers
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Infrastructure? No Offer Description Full time, fixed term for 2 years with the possibility of extension Join the School of Electrical and Computer Engineering and contribute to pioneering research redefining