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PhD studentship: Discovery of rational therapeutic biomarkers in breast cancer by systems pathology and deep learning Supervisor: Dr Hamid Raza Ali Department/location:Cancer Research UK Cambridge
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Epidemiology of Malaria), led by Aimee Taylor. Using simulation-based inference (SBI) with deep learning, UniGEM aims to build a neural network to estimate epidemiological parameters of P. falciparum
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 5 hours ago
mathematical formalization AI / machine learning / deep learning background some Python / PyTorch experience scientific curiosity, taste and autonomy in explorative tasks and problems References [1] Toussaint
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with deep-learning, UniGEM aims to build a neural network to estimate epidemiological parameters of P. falciparum, the deadliest malaria parasite species (read [1] to learn more about the ideas behind
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research university located in the heart of Detroit, Michigan where students from all backgrounds are offered a rich, high-quality education. Our deep-rooted commitment to excellence, collaboration
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Staff - Non Union Job Category M&P - AAPS Job Profile AAPS Salaried - Development & Alumni Engagement, Level A Job Title Development Coordinator, Library Department Development Library Compensation
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Staff - Non Union Job Category M&P - AAPS Job Profile AAPS Salaried - Development & Alumni Engagement, Level A Job Title Development Coordinator, Faculty of Medicine Department Development Medicine
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, Electrical Engineering, or a related discipline. Strong research background in one or more of: Computer Vision Machine Learning Deep Learning Video Understanding Multimodal AI Excellent programming skills in
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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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, visiting researchers, master's students, etc.) Research Context Recent advances in mobile robotics have been driven by remarkable progress in perception, deep learning, and control. However, current robotic