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Python and modern machine‑learning development, including version control (Git), testing, and reproducibility; experience with cloud-based solutions (e.g., Azure) is a plus. In our international working
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with deep generative models (VAEs, GANs, diffusion models) or probabilistic modelling is a strong plus. You have good programming skills in Python and experience with a deep learning framework such as
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-driven modelling. Experience with numerical modelling, simulation, optimization, control, or engineering-data analysis. Good programming skills in Python, MATLAB/Simulink, or a comparable scientific
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, parabolic equations, ray-tracing. Skills: excellent computational skills: Python, Fortran, HPC. Language skills: Fluent in English, Spanish is not required but advantageous. Specific Requirements We
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perception, optimization, or control will be an advantage. The candidate should be comfortable with scientific programming, for example in Python and common machine-learning frameworks such as PyTorch
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, longitudinal modelling, machine learning and multivariate approaches. Proficiency in programming (e.g., MATLAB, Python, or R), handling large datasets, and working with complex analysis 2 pipelines is an
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learning, computing, data science, biomedical engineering, or a related field at the level of a master degree Programming skills (Python) and experience with common machine learning platforms Experience with
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, granularity, semantics, attributes) using QGIS and Python for data exploration and preprocessing - designing an approach for automatic change detection using AI techniques (classification, clustering
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-related discipline. 2) Strong programming ability in optimisation or machine learning (e.g., Python/Matlab/C++; PyTorch/TensorFlow). Experience in signal processing/wireless or SDR/GPU prototyping is a plus
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data science, biomedical engineering, technical medicine, or a related field. You should have strong programming skills (Python, PyTorch), deep learning knowledge (multimodal learning, longitudinal