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achieved by combining state-of-the-art algorithms from multiple domains such as evolutionary algorithms, reinforcement learning, and control theory. The main responsibility of the successful applicant will
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achieved by combining state-of-the-art algorithms from multiple domains such as evolutionary algorithms, reinforcement learning, and control theory. The main responsibility of the successful applicant will
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complex research projects involving multiple interdependent components. Experience in programming (python) and applying AI-assisted technologies to streamline research and analysis workflows is highly
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such as python, as well as wet lab skills for handling and producing protein, and performing biophysical assays to study phase separation. Find out more about our group here: https
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in Environmental Modelling, Land Use modelling or another relevant field, with clear skills highly complementary to those of the JPP4JL research team Proven ability to write code in R or python
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decision-making. The group is actively involved in multiple research areas, including: · Frontier beam and MIMO technologies for swarm control and ISAC in 6G communications and edge computing