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Field
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. The high-level goal of the project is simple: to use anatomical knowledge and existing knowledge as training data for deep neural networks (instead of manual annotations). The research will be conducted
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the genotype in a few large-effect genes including SIX6 and VGLL3. How genetic variation in these regulatory proteins translates through gene regulatory networks into life history variation remains largely
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net zero aviation. This project will explore the science of novel cooling technologies, such as phase change materials and heat transfer enhancement, for the air systems used to condition the turbine
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. These are essential components for optical quantum computers and quantum networks, where one bit of information is encoded in the quantum state of a single photon. You will be part of a team of 10-12 people between
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | 25 days ago
Job Code: 21-25 Job Offer from July 31, 2025 The Max Planck Institute for Multidisciplinary Sciences is a leading international research institute of exceptional scientific breadth. With more than
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, University of London in August 2024. As a PhD candidate, you'll become an integral part of the School of Science and Technology (proud member of the Alan Turing University Network) and be supervised by leading
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inductive biases, we aim to identify key mechanisms that drive rapid learning in the visual system. The goal is to create a robust mechanistic neural network model of the visual system that not only mimics
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networks worldwide. You will work across the Faculty of Arts and the Faculty of Spatial Sciences, but you will be officially appointed at the latter. The Faculty of Spatial Sciences of the University
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University/NL. The successful candidates commit to actively participate in networking including regular research visits to the partner laboratories. Requirements: university degree in chemistry or physics and
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of Science and Technology (proud member of the Alan Turing University Network) and be supervised by leading experts in machine learning for healthcare. You will also be affiliated to the School of Health