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at a reduced cost. In this context, we are looking for a highly motivated postdoctoral researcher to join our team at the CRSA to develop AI models, specifically deep learning approaches, to analyze and
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, and deep learning. A Ph.D. in Statistics, Mathematics, CS/EE (with a focus on statistics/machine learning) or a directly related field at the time of appointment is required. The successful applicant
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frameworks such as GTSAM, G2O, or similar; computer vision frameworks like OpenCV; and/or deep learning frameworks such as PyTorch and TensorFlow Prior experience with industry or publicly funded research
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central area of expertise. The successful candidate shall demonstrate deep knowledge of LCA methodology and tools, and show strong competencies in methodological development and application across various
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on histopathology image data. As a postdoctoral researcher you will be involved with development and validation of AI/deep learning solutions for precision medicine and patient stratification (patient outcome
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are comfortable navigating complex HPC environments and wrangling large datasets. You have experience with modelling through state-of-the-art machine and deep-learning methods and with hands
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knowledge about recent neural network architectures for machine learning (e.g., CNNs, RNNs, GANs) have considerable experience with a deep learning framework are curious about the cross-field between signal
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Control engineering (experience with nonlinear systems is a plus) Machine learning and deep learning in context of physical systems Programming skills are required, with Python experience preferred. A good
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and great opportunity of interdisciplinary training in machine learning and functional genomics. The project combines cutting-edge computational approaches, especially state-of-the-art machine learning
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artificial intelligence techniques: deep learning or swarm intelligence is a plus but is not required. The annual base salary range for this position is $85,000 - $100,000. When extending an offer