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machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run
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. Qualifications: PhD in machine learning, with experience in applications in computer vision or medical image analysis. Strong publication record in top venues (e.g., CVPR, MIDL, MICCAI, IPMI, PAMI, TMI, MIA
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are looking for candidates to have the following skills and experience: Essential criteria PhD qualified in mathematical, physical or computational sciences Experience in using machine learning methods
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scholar to conduct research at the intersection of robotics, controls, and machine learning. The successful candidate will help shape next-generation approaches for autonomous multi-robot systems
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, machine learning, Experience in human electrophysiological research is a plus, experience in intracranial human research large plus, Knowledge of cognitive system is a plus, knowledge of neuronal basis
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therapeutic targets. These efforts will generate large-scale, rich perturbation datasets, requiring the development of sophisticated approaches and methods incorporating facets such as machine learning and
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, including use of scientific libraries (e.g., NumPy, Pandas, Matplotlib, etc). Experience with machine learning (e.g., Scikit-learn, PyTorch) or physics-informed neural networks for thermal systems is a plus
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performs MRI research and development of advanced multiparametric methods for the evaluation of primary and metastatic brain tumors. Recent work incorporates machine learning methods to advance
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piglets who are unable to acquire own mothers’ colostrum. The majority of the experimental in vivo work is located at Frederiksberg Campus, albeit but with some investigations under commercial farming
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considers factors such as (but not limited to) the specific grant funding and the terms of the research grant when extending an offer. PhD apply on Interfolio site For people in the EU, click here