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following areas: Strong foundation in machine learning, optimization, and deep learning algorithms, including Transformer architectures. Hands-on experience or solid theoretical knowledge of LLMs/SLMs
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mechanisms, optimisation algorithms and renewable energy systems WORK-LIFE BALANCE: Optimal conditions for balancing work and private life, as well as a family-friendly company policy. The option for flexible
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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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(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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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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university community. Key Responsibilities: Conduct comprehensive literature reviews to identify existing solutions and their limitations, and develop advanced NLP algorithms for multimodal data. Design and
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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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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
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at the interface of computational systems biology and mathematics/statistics with a strong attitude to open research software development. For more information visit http://www.fz-juelich.de/ibg/ibg-1/modsim
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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