19 algorithm-development-"St"-"St" PhD positions at University of Twente (UT) in Netherlands
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trading decisions under high price volatility. This PhD position focuses on designing, developing, and evaluating self-learning energy trading algorithms that are able to cope with these challenges. By
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through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description This PhD project aims to develop a
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require efficient numerical algorithms to be practical and to enable robust optimization. Therefore, in this project you will: Develop efficient numerical methods and strategies to solve the electromagnetic
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seeking for motivated candidates that are interested in developing computer models of the composite human neuro-muscular system that combine detailed musculoskeletal geometries, muscle-tendon models and
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, device modelling/simulation aspects of new tunnelling devices. By using dedicated electrical dc and RF measurement equipment within our measurement & test centre, you will develop and carefully analyse
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description We are developing a platform for studying protein dielectrophoresis
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with cross-collaboration opportunities” (HARMONI). The project is led by IDENER (Spain) and has 13 participating organisations from 7 European countries. The overall aim of HARMONI is to develop a
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to develop decision-support tools for AI adoption; A 4-year fully funded position, plus benefits, training, and career development opportunities; Supervised by experienced scholars, embedded in the HBE section
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circular way can affect each other. While national strategies and missions give directions to address such grand societal challenges, local decisionmakers, such as municipalities and project developers, need
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of Twente and the Infomatter group at AMOLF. The SMIP project aims at revolutionising computing by developing adaptive, smart materials that combine memory and learning directly within their structure