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results in restricted formal contexts. The objective of the proposed PostDoc is to work at the intersection of model counting and machine learning, with the aim of significantly improving counting
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Copenhagen, and postdocs will work under the academic leadership of Professor Johannes Bjerva https://bjerva.github.io/ . The NLP group is a rapidly expanding research environment with strong activities in
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investigate out-of-equilibrium dynamics in high-dimensional disordered systems (including models relevant to machine learning and optimization) by characterizing the fixed points (metastable states, attractors
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patients with pancreatic cancer and other aggressive tumor types. The work includes statistical modelling, machine-learning and systems biology approaches to identify drivers of metastasis and treatment
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learning – and we are growing and seeking: Postdoc / PhD Student / Entrepreneurial Postdocs to join the Institute and its wider research community. We welcome applications across all areas of machine
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by ARPES, pursue scalable wafer-scale moiré epitaxy, develop epitaxial superconductors for quantum computing and integrate machine learning for automated high-throughput MBE. We are particularly
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Inria, the French national research institute for the digital sciences | Grenoble, Rhone Alpes | France | 9 days ago
communication, sociable with an appetite for working in a group. Additional skills appreciated: rigorous, organized, curious, autonomous, proactive and dynamic. A specialization in optimization, machine learning
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 3 hours ago
-processing and machine-learning algorithms that account for skin pigmentation, low perfusion, and motion. Work with UNC clinical collaborators on IRB-approved human-subjects validation studies, including
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ability to acquire new skills and technologies. Outstanding spoken and written communication skills are essential. Qualifications requirements Appointment as Postdoc presupposes scientific qualifications
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within the Division of Artificial Medical Intelligence of Department of Ophthalmology in the University of Colorado School of Medicine. We focus broadly on quantitative and machine learning techniques in