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statistical and machine learning to real life problems, using a popular computer language (e.g. Matlab, Python), and familiarity with topological and geometric data analyses. Candidates will have excellent
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Science Park. The post is funded by Innovate UK and is fixed-term to 30th April 2026. The CEBD project is an ambitious programme to develop the first category enhanced battery powered eVTOL. The project
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should have a recent doctoral degree in electrical engineering, control engineering, or a related field. For the physics-informed AI position, a doctoral degree in computer science or applied mathematics
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to the study and teaching of the language and literature of ancient Greece and Rome, including Late Antiquity, as well as the late, medieval, and Neo-Latin language and literature. At the core of the program is
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with IoT, edge computing, and cloud integration in rural or resource-constrained settings. Proficiency in MATLAB/Simulink and AI/ML tools like TensorFlow or PyTorch. Excellent programming skills (e.g
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, paternity and adoption pay Employee assistance programme: Staff Support Service Discounted medical insurance Our commitment to Equality, Diversity and Inclusion As London’s Global University, we know
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interdisciplinary research programme involves national and international collaborators. We are a vibrant, enthusiastic, innovative and strategic enterprise with an internationally leading position to make a real
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numerical modelling. Ability to participate in research meetings to troubleshoot research problems and discuss the direction of research. Skills Fluency in at least one scientific computer language (e.g., C
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"Mathematical Data Science" research group at the University of Vienna (led by Prof. Dr. Philipp Grohs) and the "Computational Partial Differential Equations" research group at TU Wien (led by Prof. Dr. Michael
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faculty. You participate in research projects and studies. Candidate Profile: You might have a background in computational chemistry, theoretical condensed matter physics, computer science, or a similar