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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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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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university master's degree level or equivalent. Driving licence and car Not to have a previous PhD degree. Proficiency in English Strong teamwork skills, ability to adapt to multidisciplinary environments and
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UNIVERSIDAD CATÓLICA DE MURCIA - FUNDACIÓN UNIVERSITARIA SAN ANTONIO DE MURCIA | Spain | 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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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
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composites for enhanced durability, performing microstructural analysis and mechanical testing. Topology Optimization & AI Integration: Use AI and machine learning to guide structural and topology optimization
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combines synthetic biology, machine learning, and biosensor and pathway dynamic regulation design to produce next-generation bio-based chemicals. The Computational Synthetic Biology group (CSBG), led by Dr
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analysis, including statistics and machine learning techniques. Proficiency in scientific programming, especially Python and/or Matlab, and experience in shell scripting. Excellent written and oral
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) Positions PhD Positions Country Spain Application Deadline 31 Jan 2026 - 23:59 (Europe/Madrid) Type of Contract Temporary Job Status Full-time Hours Per Week 38,5 Offer Starting Date 1 Feb 2026 Is the job