8 machine-learning-modeling-"https:"-"Computer-Vision-Center" Postdoctoral positions in Spain
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Employer
- BARCELONA SUPERCOMPUTING CENTER
- Biobizkaia Health Research Institute
- Consejo Superior de Investigaciones Científicas
- FUNDACIO INSTITU DE RECERCA EN ENERGIA DE CATALUNYA
- Institut Català de Nanociència i Nanotecnologia
- Institut de Robòtica e Informàtica Industrial CSIC-UPC
- Universidad Nebrija
- Universidad Politecnica de Cartagena
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Field
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software. (0-35) Experience in the application of advanced machine learning techniques (e.g., graph neural networks, reinforcement learning, probabilistic models, or latent representations) to biomedical
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and modelling of omics, clinical and imaging data, development of reproducible pipelines, application of machine learning techniques, integration of multi-modal data, scientific publication and
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the interplay between mutations, energetics, and evolutionary constraints, including epistatic effects. · Developing or applying machine learning approaches to predict or redesign frustration patterns in proteins
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expertise in machine learning or computational modelling who are eager to advance conceptual innovation toward practical industrial deployment. Qualifications PhD in Computer Science, Machine Learning
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platforms. Experience in development of digital twins or physics-informed machine learning models. Experience in programming (e.g., Python or equivalent) and development of control or data acquisition
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Simulations (INMA, Zaragoza) Build and maintain software infrastructure for modeling quantum systems with machine learning tools. Investigate neural-network-based representations of many-body quantum states
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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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experience with DFT codes will be very highly valued. • Knowledge of chemical reactions and how to model them through computer simulations is highly valued. • Knowledge of classical molecular dynamics