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9 Mar 2026 Job Information Organisation/Company CSIC Research Field Technology » Biotechnology Biological sciences » Biological engineering Mathematics » Applied mathematics Computer science
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PhD Studentship: Green vs. Non-Green Innovation: The Role of Regulatory Policies and Market Dynamics
equivalent) is required. Candidates from disciplines such as mathematics, statistics, computer science, economics, or related quantitative fields are strongly encouraged to apply. While applicants need not be
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degree (honours) or master degree by research in either: mechanical engineering biomedical engineering chemical engineering civil engineering applied mathematics applied physics related disciplines
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discipline) Science or applied science Mathematics or data science Computer science Environmental or sustainability studies Design, manufacturing, or technology fields Applicants should demonstrate: A strong
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/Qualifications Master’s degree in theoretical physics, with a strong background in quantum field theory, high-energy particle physics, and in particular quantum chromodynamics Solid mathematical skills Experience
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should have the following qualifications: MSc. degree in computer science Solid mathematical and analytical skills Solid knowledge and skills in time series machine learning Significant experience in
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robust mathematical frameworks to solve real world problems with our industrial collaborators at Rolls-Royce. The Challenge Modern aerospace systems are undergoing a digital revolution. Future aircraft
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Institute for Industrial Mathematics ITWM, we see our task as further developing key technologies, providing innovative impetus and implementing these in practice together with industry partners. In doing so
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departmental duties, up to a maximum of 20 per cent of full-time. Your qualifications You have graduated at Master’s level in Electrical Engineering, Computer Science, or Applied Mathematics, with a minimum of
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at the intersection of theory and implementation, developing rigorous mathematical foundations while validating the proposed methods on robotic platforms such as aerial or ground autonomous systems