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. Proficiency in algorithm development using Python will be advantageous Where to apply Website https://www.timeshighereducation.com/unijobs/listing/407953/research-fellow-ai-… Requirements Additional Information
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associate will work both independently and collaboratively to develop and apply novel deep learning algorithms and/or computational chemistry methods for small-molecule drug discovery targeting RNA
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improvements and algorithmic decisions. Collaborate with entomologists and field teams to improve data collection, labeling, and training dataset quality. Contribute to publications and presentations describing
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' premises in Nelson, Lancashire. To find out more about ELE Advanced Technologies, go to https://eleat.co.uk/. Qualifications we require: Hold a minimum 2:1 degree in a relevant field such as Electronic
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DC-26094– POSTDOC/DATA SCIENTIST – AI-DRIVEN CLIMATE RISK MODELLING AND EARLY WARNING SYSTEMS FOR...
: https://www.list.lu/ How will you contribute? You will be part of LIST’s Remote sensing and natural resources modelling group Embedded in the Environmental Sensing and Modelling (ENVISION) unit
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excitations and excitonic effects using advanced Wannier-based methods * Quantum transport in polymer materials with electron–phonon coupling Full details and application instructions: https://www.ch.nat.tum.de
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rolling basis with start dates as early as 1/1/2026 and as late as 3/1/2026. Group or Departmental Website: https://simpsoba.su.domains/ (link is external) How to Submit Application Materials: Please upload
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(Anthropic, OpenAI). Experience with graph algorithms or NetworkX. Familiarity with adaptive learning or educational technology. Experience with WebAssembly technologies (Pyodide, WebR). OAuth2 authentication
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, modulation classification, sensing, and adaptive spectrum optimization in diverse operational environments. Your work will focus on modeling and algorithmic aspects related to the development of highly
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saccades oculaire, scores EVA/Borg >6) ; (iii) Validation de l'efficacité de l'adaptation par algorithme des séances d'activités physique via une étude randomisée contrôlée sur 6 séances avec évaluation de