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represents a major bottleneck for the study of complex catalytic interfaces. Objectives The objective of this PhD project is to develop data-efficient machine learning strategies to study CO₂ hydrogenation
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offers and actions on https://cluster-ia-enact.ai/ . You will work in a rare environment at the intersection of frugal AI, analog computing, reconfigurable electronics and THz imaging. The PhD is directly
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direct metal-protein interactions in cell is key to answer these questions, yet it is also a challenge due to the labile character of these interactions. Project: We aim to identify the protein interactome
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Adaptive Learning in Brain-Robot Interactions School of Electrical and Electronic Engineering PhD Research Project Self Funded Dr Mahnaz Arvaneh Application Deadline: Applications accepted all year
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Advanced brain-computer interface School of Electrical and Electronic Engineering PhD Research Project Self Funded Dr Mahnaz Arvaneh Application Deadline: Applications accepted all year round
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of results at conferences interaction with team members and international collaborators Required skills : Degree : PhD in computer science, machine learning, or computational biology We expect a candidate with
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, see https://www.ntnu.edu/studies/phiot . As a PhD Candidate, you are obligated to participate in an organized PhD program during the employment period. A condition of appointment is that you are
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is actively promoted by the Faculty of Science, fostered under the University-wide six Interdisciplinary Labs (https://interdisciplinary-research.hkbu.edu.hk/), and supported by state-of-the-art
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Sorbonne Université SIS (Sciences, Ingénierie, Santé) | Paris 15, le de France | France | 22 days ago
, charge, hydrophobicity) and (ii) probing peptide-surface interactions at the single-molecule level. Scientific objectives This PhD project aims to extend this approach along two complementary axes. A
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the interface of machine learning and biology (tools developed by the team: https://github.com/cantinilab ). The team is composed of 8 people : 3PhD students, 3 post doc, 1 research engineer and 1 assistant