92 parallel-computing-numerical-methods-"Prof" PhD positions at Technical University of Denmark
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research. Successful applicants will ideally have: A relevant MSc degree in computer science, data sciences, applied mathematics, statistics, operations research, control, electrical engineering, energy
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engineering, statistics, physics, mathematics, data science, informatics or similar degree with an academic level equivalent to a master's degree. The candidate should preferably have: Dedication and the desire
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qualifications As our new colleague in our research team your job will be to develop novel computational frameworks for machine learning. In particular, you will push the boundaries of Scalability, drawing upon
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computer science and control systems architecture, advancing all the above disciplines. Building energy flexibility is an important resource for balancing and load shifting in energy networks, especially
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level equivalent to a two-year master's degree in Electrical Engineering, Computer Science, Robotics, Safety Engineering, or related fields. Approval and Enrolment The scholarship for the PhD degree is
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Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. The position is part of DTU’s Tenure Track program. Read more about the program and the recruitment process
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smarter food regulation and enhance microbial food safety within Denmark’s small-scale food processing sector. You will work closely with researchers from DTU Food, DTU Compute, and DTU Management
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of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education . We offer DTU is a
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academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme
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(120 ECTS) in chemical engineering, computer science, or a related discipline Some familiarity with ontologies, semantic data formats, knowledge graphs, and technologies such as OWL, RDF, SPARQL