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Field
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collaborators that: Negotiate more effectively by anticipating the downstream effects of each statement. Support complex decision-making in domains where success depends on multi-step strategy. Learn to adapt
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objects, by embedding them into a 2 or 3-dimensional space through a representation learning algorithm, has been widely used for data exploratory analysis. It is particularly popular in areas such as
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recruiting and selecting staff and students. You will collaborate with a team of clinicians (urologists/pathologists), experienced researchers with backgrounds in image analysis, machine learning, pathology
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This position is part of the NWO KIC Smart Materials project, Smart Materials for Information Processing, in collaboration with the NanoElectronics (NE) group at the University of Twente and the
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Description We are seeking a motivated new PhD candidate who wants to join an exciting collaborative research program within the VIB-Center for Inflammation Research between the Guilliams and
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Description We are seeking a motivated new PhD candidate who wants to join an exciting collaborative research program within the VIB-Center for Inflammation Research between the Guilliams and
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Max Planck Institute for Terrestrial Microbiology, Marburg | Marburg, Hessen | Germany | about 3 hours ago
Microbiology, Immunology, host–microbe crosstalk, or infection biology, this is a fantastic opportunity to pursue cutting-edge research in a highly collaborative and interdisciplinary environment. What we offer
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Your Job: Adaptive Control Theory (ACT) provides mathematically grounded and robust learning rules, prescribing that neurons should be diffusively forced toward a teacher trajectory and achieve
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learning, image analysis, and advanced computing to study relationships between structure and function. Keywords: Human Brain, 3D Atlas, Deep Learning, Temporal Lobe, Brain Function Entry Requirements
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of Prof. Dr. Frank Cichos and Dr. Nico Scherf (Max Planck Institute for Human Cognition and Brain Sciences). The position is part of a collaborative project in the Center for Scalable Data Analytics and