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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | 3 months ago
. The successful candidate will be expected to carry out the following scientific activities: Application of advanced Machine Learning, Deep Learning, reduced-order modelling, and physics-informed/-guided modelling
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. Applicants must have excellent skills in oral and written English. Fluency in a Scandinavian language is an advantage. All our staff is given the opportunity to attend courses in order to learn Norwegian and
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doctoral programme in Technology within three months of starting in the position. (https://www.usn.no/english/research/postgraduate-studies-phd/our-phd-programmes/technology/). The doctoral programme
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working conditions and attractive benefits. Equality, diversity and equal opportunities are essential to quality and form an integral part of KTH’s core values as a university and public authority. Learn
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processes. • Apply machine learning techniques and advanced statistical analysis to extract knowledge from complex datasets. • Participate in the evaluation and optimisation of high-performance scientific
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development have been set-up to respond to these societal issues. Scientific supervisor: Thomas Berthelon - MOST team ([email protected] ) Where to apply Website https://emploi.cnrs.fr
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are the same. You will have the opportunity to share your ideas, develop yourself professionally, and acquire new skills. Innovation and collaboration are at the heart of our work. You will be part of
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for using AI to develop social engineering attempts. This project combines human subject research of learning and decision making, Human-Computer Interaction, and the advancement in AI methods
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unique experimental platform developed in the Bakshi Lab (https://www.bakshilab.net/ ) that enables time-resolved measurements of individual bacterial cells throughout the phage infection process. The post
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@aalto.fi . In any question regarding the recruitment process, please contact HR Advisor, [email protected] . Learn more about the TSirc research group: https://kwantaekim.github.io Want to know more about us