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Northeastern University London > Network Science Deadline: 10th of April 2024 Funded PhD Project (UK or International Students) Funding provider: Northeastern University London (NU London) Subject
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of Contract To be defined Job Status Full-time Hours Per Week To be defined Is the job funded through the EU Research Framework Programme? Not funded by an EU programme Is the Job related to staff position
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strengths of the position The main goal of this PhD project is to develope a deep learning framework for the design of cyclic peptides. This project has an important impact on designing theraputics to fight
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, driving the seamless interaction and collaboration between diverse data sources, software/hardware systems, applications, devices, and enterprises. Managing interoperability sits at the heart of this
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as a PhD candidate and work with Dr Artem Kaznatcheev ! Your job You have the opportunity to define your own research problems and tools based on your interests and skills (in consultation with Dr
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Carl von Ossietzky University Oldenburg | Oldenburg Oldenburg, Niedersachsen | Germany | about 1 month ago
for the Atmospheric Boundary Layer” as a part of the AptWind Marie Skłodowska-Curie Doctoral Network. The PhD candidate will be employed 50 % of the time at the University of Oldenburg in Germany and 50 % at Siemens
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Banks (BAMB), representing building products and material constituents in (Digital) Product Passports, defining measurement indicators for circularity (e.g., Building Circularity Index (BCI), Material
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(UTC) Type of Contract To be defined Job Status Full-time Hours Per Week To be defined Is the job funded through the EU Research Framework Programme? Not funded by an EU programme Is the Job related to
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Software-defined and programmable networking is a key enabling technology to support 6G in achieving their promises of increased scalability and flexibility at a lower cost. Deep network
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Software-defined and programmable networking is a key enabling technology to support 6G in achieving their promises of increased scalability and flexibility at a lower cost. Deep network