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is required The candidat must have a PhD in computer science, machine learning, or computational biology The position is initially for 12 months with the possibility of extension. Application : send
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the subject. More precisely: PhD degree in computer science, machine learning, computational biology, or a closely related field Strong research track record demonstrated by publications in
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scientific publications during the project. Methods / Means Python, PyTorch, self-supervised learning, multi-sensor data processing and Git. Applicant Profile PhD in machine learning, applied mathematics
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subsequent PhD in computer science (or a related field). Rich experience in devising machine learning models, methods, and algorithms for computer vision, image processing, imaging, and/or physics
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are seeking a highly motivated early-career scientist to develop cutting-edge machine learning approaches for understanding and designing pathogen antigens. This is a unique opportunity to help shape
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contact Dr. Sandrine Medves (email address: ). Your profile Core qualifications: PhD in relevant domains including Artificial Intelligence, Machine Learning, Deep Learning, or High-Performance Computing
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Postdoc – Advanced characterization of the stability of tandem photovoltaic cells under illumination
skills: Python programming, Silvaco (basics), machine learning, scientific english Soft skills: curiosity, analytical skills, ingenuity, proactive in suggesting ideas Position location Site Grenoble Job
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AI and machine learning applications in complex diseases such as Cancer, Alzheimer's, Parkinson's and Cardiovascular diseases. Your role You will work within a multidisciplinary environment alongside
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EN FR Go back Scroll to top Share (PhD) Mechanisms of temporary hearing loss after an acoustic trauma Postdoctoral Position in AI, Machine Learning and Auditory Neuroscience © Research Job Postdoc
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EN FR Go back Scroll to top Share Postdoc position in Machine Learning for Integrative Genomics (PhD) Impact on presbycusis of repeated acoustic trauma © Charles DAUGUET, Institut Pasteur HIV