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- Barcelona Beta Brain Research Center
- Autonomous University of Madrid (Universidad Autónoma de Madrid)
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to the topic, including food safety, microbiology, computational biology, machine learning, artificial intelligence, data science, or other related scientific fields. Familiarity with data-driven
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for the Rural Spain: Adaptation of Large Language Models (LLMs) and Speech Recognizers to Rural Speech" (SI4/PJI/2024-00237), granted in the 2024 call for R&D Project Grants for Emerging PhDs by the Universidad
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infrastructure (e.g. Observatorio del Roque de los Muchachos) Hands-on training in cutting-edge techniques, from detector R&D to advanced data analysis and machine learning. Attendance to international
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architectures for TTS and ASR Entrenamiento de modelos a gran escala utilizando frameworks modernos de deep learning / Training large-scale models using modern deep learning frameworks Publicaciones en
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of Spanish (not required but valued for teaching and policy dissemination in Spain). Experience with AI-based research workflows, machine learning techniques applied to financial data, or modern
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of artificial intelligence (AI) and biomedical engineering. Research directions include deep learning, natural language processing, brain–computer interfaces, and their applications in disease prediction, drug
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hypotheses. The candidate will apply machine learning models to clinical and omics data for classification tasks. We are looking for highly motivated and organized candidates with good communication skills
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). Familiarity with machine learning techniques, particularly LSTMs or other deep learning architectures. Experience with large datasets, geospatial analysis, or database development. Knowledge of ecological flows
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+ EDX · Fully Automated FIB Helios 5UX · FEI SEM Quanta and SEM Magellan Requirements: · Education: PhD in Physics, Materials Science, Nanoscience, Computer Engineering, Data Science. · Knowledge: Deep
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predictive modelling; Bioinformatics and Knowledge Graphs (visualization and reporting); AI-based data integration across cohorts (with federated machine learning); Contribute to ongoing projects, such as: o