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Field
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related fields. Experience in Machine Learning/AI, mathematical, computational and statistical training are also advantageous. About the employment The employment is a temporary position of two years
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, machine learning, data visualization, digital hermeneutics; an interest in media history or history of technology would be an asset Fluency in English and good knowledge of French or German Ability to work
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Agroecology Seeking a postdoctoral associate with PhD research and training in social science fields related to transdisciplinary agroecology, such as critical agrarian studies, sociology, political ecology
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topics: Free space optical communication Visible light communication DSP for coherent optical communication Machine learning and AI-native physical layer design Optical reconfigurable intelligent surfaces
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: On site Car Parking On site dining facilities On site TFI Bike Sharing Station Eligibility criteria Essential: Hold a PhD in a relevant discipline at the contract start date. Relevant Research Experience
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electron ground states. Another promising route towards physical implementations of energy-based machine learning and neuromorphic hardware is to utilise material platforms that exhibit multiwell behaviour
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 17 days ago
, CIRAD AMAP, CIRAD PHIM, CIRAD PBVMT, INRAE ePhytia, INRAE IGEPP, INRAE LISAH, IRD EGCE, IRD IEES, Univ. Paris Saclay, TelaBotanica). This is a postdoctoral position in Machine Learning, more
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., knowledge representation and reasoning) and bottom-up (e.g., machine learning) methods to study the representation of geographic categories and processes. While we welcome applicants from a broad range of
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supersonic and hypersonic flows, as demonstrated by application materials. Familiarity with machine learning or data-driven modeling approaches in fluid dynamics, as demonstrated by application materials
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that interaction represents the foundation of active learning and fosters acquisition and retention of knowledge, as opposed to passive reception in traditional teaching. Some benefits of MR are now well established