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Field
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, including intracranial EEG (iEEG/SEEG), local field potentials (LFPs) and single-unit recordings. The position has a strong focus on scientific software development in Python, data engineering and signal
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) to soft matter or related systems; basic knowledge of scattering data modelling is essential. Data analysis skills and programming experience in Python or MATLAB. Ability to work effectively with multi
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scientific programming (Python, Matlab, R) Knowledge of process engineering (heat and mass transfer) and/or food chemistry. Desired qualities: Scientific curiosity and ability to take the initiatives Autonomy
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ExperienceNone Additional Information Eligibility criteria PhD in Earth/environmental sciences/remote sensing with applications in AI Linux, Python, good command of English Additional comments Nothing to mention
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bacterial genome analysis and comparative genomics. * Skills in bioinformatics applied to genomic data analysis. * Experience in data analysis and visualization, particularly using R and/or Python. * Ability
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Physics, Applied Mathematics, or Computer Science, with experience in deep generative models (VAE, diffusion) and Python/PyTorch. Applications from statistical physicists are welcome. STILL HESITATING? The
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science, instrumentation and electronics. Have a good command of the Python language or equivalent. Be sensitive to the requirements related to medical device developments. Be rigorous, methodical and have a strong
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biology, bioinformatics, infectious-disease epidemiology, evolutionary or ecological biology, or a closely related field. Strong programming skills (R, Python, and/or other) Familiarity with version control
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Madagascar, and ULTIMASero, a large cohort study with collaborators in Senegal, Cameroon, and Madagascar. Required skills: • Strong programming skills (R or Python or other) • Familiarity with Git / GitHub
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, or computer science. Core competencies: solid background in quantum many-body physics strong programming skills (Python required, Rust a plus) experience with tensor networks, variational Monte-Carlo, machine learning