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técnicas de machine learning e IA. Sólidos conocimientos en análisis y tratamiento de datos, programación y desarrollo de modelos analíticos. Experiencia con bases de datos y herramientas de análisis
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analysis, computer vision, or machine learning, with a clear interest in developing image analysis algorithms and an affinity with medical topics. Good communication and organizational skills are essential
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to Principal Investigator level. Research areas include: Population neuroscience and multimodal neuroimaging Computational psychiatry and imaging genetics AI and machine learning for brain science Multi-omics
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Institut d’Investigació Biomèdica de Girona Dr. Josep Trueta (IDIBGI-CERCA) | Spain | about 2 months ago
practical knowledge of statistical and programming packages is mandatory, including R, Python, and/or SQL. Extensive experience with advanced statistical techniques and algorithms, such as Machine Learning
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fellows will receive joint mentorship from leading experts in metabolic biology, AI and machine learning, drug delivery, and translational medicine, while maintaining full academic independence in research
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, engineering or physics. Knowledge: Computational programming, machine learning, quantum transprot, device simulation. Professional Experience: use of device simulation codes applied to 2D materials. Personal
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laboratorio. Experiencia en programación en Python y técnicas de machine-learning. Master’s degree in biomedicine, biotechnology, or a related field. Knowledge of laboratory techniques. Experience in Python
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for a short-term 2.5-month postdoctoral position (full-time) focused on developing and validating machine learning models that predict soil health and crop performance. The position will exploit datasets
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contribute to project reporting. Work with the interdisciplinary team of the group (theory, computation, machine learning) and support junior researchers on SOT-related topics. Requirements: Education: PhD in
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Analysis Plans. •Experience with missing data methods and causal inference. •Experience with Bayesian methods and machine learning approaches. •Experience with REDCap and clinical research databases