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University of Lille offers a 34-month fixed-term contract researcher position to work on the recently funded project ACCTS (“Assessing cirrus cloud thinning strategies by learning from aerosol-cirrus
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, the Netherlands, Germany, and beyond) by the company Quandela (www.quandela.com ). Using such sources, the first on-chip photon manipulation protocols have already been demonstrated with about ten photons. To move
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, statistics, machine learning and deep learning. The project Motivation: Interpreting the genome means modeling the relationship between genotype and phenotype, which is the fundamental goal of biology
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experimental parameters (time, temperature). To optimize these parameters, active learning techniques based on Bayesian optimization will be applied. In situ or ex situ characterizations (FTIR, ¹¹B/¹H NMR, HP
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of autonomous mobile machines integrating perception, reasoning, learning, action and reaction capabilities. The team's main research areas are: architectures for autonomous robots, human-robot interaction
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developed within the project. - Assure the methodological and scientific coherence between the two center of the Synergy project. - Co-supervision of the PhD students and lab-development co-coordination
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FieldPsychological sciences » PsychologyYears of Research Experience1 - 4 Additional Information Eligibility criteria * PhD in Neuroscience, Biomedical Engineering, Computer Science, or related field. * Strong
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FieldMathematicsYears of Research ExperienceNone Additional Information Eligibility criteria Academic: PhD in applied mathematics, computer science, or medical physics. Scientific interests: applied mathematics
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defined based on your profile and skills, ensuring a strong fit with the project's needs and your own expertise. As a key collaborator, you will work alongside me and two PhD students, taking the lead on
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be supervised by Johan Decelle. There will be numerous interactions and synergies with national and international partners. To learn more about the project, several publications are available