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Field
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the first year of the CDT at TheUniversity of Manchester undertaking taught MSc studies and research training. Years 2 – 4: You will move to your host institute (University of Manchester, University
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to efficiently navigate high-dimensional decision spaces, leveraging open-source agent-based simulation tools to evaluate accessibility and environmental impacts of urban planning policies. You should have an MSc
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participating in teaching. Selection Criteria A MSc degree in (urban) ecology, plant sciences, microbial ecology, environmental sciences, or a related discipline Experience in designing and conducting plant
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/ Applicants must have a Master’s degree in computer science or a closely related field such as mathematics or control engineering. Due to the project’s angle, applicants should have a strong background in at
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decarbonization of existing maintenance and decommissioning of assets. Year 1: You will spend the first year of the CDT at TheUniversity of Manchester undertaking taught MSc studies and research training. Years 2
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240 higher education credits in Applied Mathematics, Applied Physics, Electrical Engineering, Mechanical Engineering, or a related field. A strong mathematical foundation and excellent academic
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the PhD, having obtained a Master’s degree in a relevant field, such as AI, cognitive psychology, mathematics, physics, (computational) neuroscience, etc.. Terms and conditions The terms of employment
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this increasingly important area of science and engineering. RAINZ_CDT Year 1: You will spend the first year of the CDT at the University of Manchester undertaking taught MSc studies and research training. You must
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Your job Are you a motivated and curious individual with a strong interest in forests, forest dynamics and climate sciences? Do you have an MSc. degree in forest ecology, earth system science
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collaborations with colleagues across domains! Selection criteria A MSc degree in Computer science, Applied Mathematics, Physics, or a related field; Good knowledge of and experienced with machine learning; Good