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laser experimentation to study and control complex nonlinear dynamics. Key Responsibilities: Develop and implement Physics-Informed Neural Network (PINN) models to simulate, predict, and analyze complex
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to investigate overwintering habits, alternate plant hosts (crop and non-crop) and potential predators, that could help with pest control. The goal of this research is to investigate overwintering habits and
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or qualifying to apply for a Chinese Medicine Practices license; Experience managing randomised controlled trials in therapeutic research for Gastrointestinal diseases is preferred; Experience with ICH-GCP
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seamlessly in the physical world through embodied robotic platforms. The PhD candidates will be part of the department’s research activities at OsloMet OceanLab, working within robotics, control, perception
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note that an appointment to posts advertised will be dependent on University approval, together with the terms of the employment control framework for the higher education sector
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modelling tools to real-world challenges in antibody engineering. The position offers the opportunity to contribute to the development of new technologies for precise control of antibody glycosylation, with
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a five-year master degree within electrical engineering, energy systems, power engineering, control and systems engineering, and/or mathematics and physics, preferably acquired recently; or who
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science; quantum many-body physics; quantum precision measurements and fundamental physics; quantum metrology, sensing, and control; and quantum chemistry and materials science. Fellowships are awarded for a
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genetic pest management. The fellow will investigate the structure, function, and epigenetic control of genes on the X and Y chromosomes of fruit flies in the insect family Tephritidae which are major
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formulation as sustainable tools for the control of insect pests of some major crops. The selected candidate is expected to: Design and develop versatile biopesticide formulations using some effective natural