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Field
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Fellow position in innovative prosthesis production. The successful candidate will work with a dynamic team of researchers to develop and optimize novel techniques for the production of prosthetic devices
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School of Medicine. The project will focus on optimization of peptide ligands targeting promising cancer antigens followed by subsequent radiolabeling and pre-clinical validation. The Beinat lab employs
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algorithms to develop cybersecurity, optimization, and control solutions for real-world grid applications. Candidates will be required to work in at least 4 of the following areas: Build, simulate, and
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related field in hand by the time of the appointment. Strong background in distributed control, optimization, or multi-agent systems. Proven track record of high-quality publications. Proficiency in
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high degree of independence and technical proficiency. Methodology and innovation: Work with the PI to develop, optimize, and document novel experimental techniques and protocols to advance the lab’s
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Internal Number: JR89928 Position Summary This position will primarily support the implementation of a newly funded National Institute of Mental Health R01 grant focused on optimizing a digital chatbot
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. Work with NSLS-II automation team and engineering support staff to develop the next generation of robotics and sample preparation protocols for XCFS. Optimize crystallization systems for XCFS campaigns
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machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run
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project. The overarching aim of this project is in the development of new knowledge and a new framework to facilitate the optimal design and life-long adaptation of civil infrastructure systems
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upgraded hadron calorimeter, trigger system optimization, and improvement of particle flow reconstruction. We are currently engaged in measurements involving the top quark, searches for rare Higgs boson