72 parallel-and-distributed-computing-"the" PhD positions at Technical University of Denmark
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process. An integral part of the project will be the development of enhanced data-driven physics methods to achieve reliable prediction of material removal rate and material removal distribution
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driving rapid growth in distributed energy resources (DERs), the electrification of transport, heating, and water systems — and the rise of hyperscale data centers. Coordinating these heterogeneous active
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Job Description Do you have a background in bioinformatics or AI/ML? Do you wish to do a PhD whereby you use your computational skills to discover new insights in industrially important bacteria
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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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undermine this future. Can you see how Machine Learning, Computer Vision, and Robotics can open up opportunities for autonomously operating agricultural robots? Are you passionate about making agriculture
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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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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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. These are essential components for optical quantum computers and quantum networks, where one bit of information is encoded in the quantum state of a single photon. You will be part of a team of 10-12 people between
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our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education . Assessment The assessment of the candidates will be made by Prof. Niels
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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