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early detection is a need that needs to be addressed using advanced sensors. The candidate will apply machine learning and IA methods to anticipate the evolution of the discharges. This project aims
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the project ‘MultiLearn: A multimodal approach to language learning: a window into the linguistic skills of children with neurodevelopmental disorders‘. The project is led by researchers Alfonso Igualada and
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, environmental, and resource economics. Ideal candidates are those wishing to acquire research experience for a subsequent Ph.D. in Economics. Due to the short term appointment, applicants must have a Spanish tax
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to support machine learning model development to accelerate materials discovery: Perform high-throughput DFT and molecular dynamics simulations to investigate the thermodynamic, structural, and electronic
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expertise in analysing complex quantitative and computational data and/or rich qualitative data. • Proficiency or skills to learn a statistical software (e.g., R, Stata, Python). • Interest in contributing
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UNIVERSIDAD CATÓLICA DE MURCIA - FUNDACIÓN UNIVERSITARIA SAN ANTONIO DE MURCIA | Spain | about 2 months ago
Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you passionate about Artificial Intelligence, Machine Learning
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PhD student position on development of innovative bifunctional oxygen electrodes for SOC technology.
on the development and testing of oxygen electrodes for SOC technology - A person who is highly motivated to learn, work in a team, showing high flexibility and initiative and ability to innovate. - Bachelor and
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characterize new reticular materials (COFs), and use them as precursor for the generation of new polymers via Clip-off chemistry. The candidate will acquire a great experience in supramolecular, reticular and
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(ICS). A scientific environment of excellence, highly dynamic, where high-end biomedical projects are continuously developed. Continuous learning and a wide range of responsibilities within a stimulating
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descriptors to support machine learning model development to accelerate materials discovery: Perform high-throughput DFT and molecular dynamics simulations to investigate the thermodynamic, structural, and