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Position: Research Associate (Postdoc) on data science and machine learning for Industry 4.0 factories
Institution: University of Luxembourg
Location: Luxembourg City, Luxembourg
Duties: Identifying and adapting data curation and sanitization techniques to the context of Industry 4.0; Comparing and complementing statistical models with ML ones; Contributing to theories, techniques and tools to ensure the secure, efficient and robust deployment of ML systems; Improving verification with traditional ML, but also deep learning; Applying these techniques to severall Cebi use cases; Publishing your research contribution in top-venues in the fields of software engineering and ML
Requirements: The candidate should possess a PhD degree (or equivalent) in Computer Science with strong programming skills; The ideal candidate should have some knowledge and/or experience in a number of the following topics: Software engineering; Machine learning and AI; Data science and statistics; IoT and Industry 4.0
   
Text: UOL04074 31-Dec-2099 About the SnT... SnT is a leading international research and innovation centre in secure, reliable and trustworthy ICT systems and services. We play an instrumental role in Luxembourg by fueling innovation through research partnerships with industry, boosting R&D investments leading to economic growth, and attracting highly qualified talent. We’re looking for people driven by excellence, excited about innovation, and looking to make a difference. If this sounds like you, you’ve come to the right place! As the successful candidate, you will join the Security, Reasoning and Validation (SeRVal) group of the SnT, under the supervision of Prof. Yves Le Traon and Dr. Maxime Cordy, working on a research collaboration between Cebi (worldwide expert company in the manufacturing of components for the automotive and household appliances industry) and SnT for conducting a full data driven process, designing an automated and scalable system to deploy, evaluate, maintain and evolve machine learning models on top of a factory equipped with monitoring capabilities (continuous sensor data collection, aggregation and exploitation). Cebi is investigating to what extent data science and more specifically machine learning could contribute to improve the efficiency of their operations, their internal processes and statistical analyses. Among various use cases, Cebi is particularly interested in conducting an in-depth analysis of production data, predictive maintenance & quality, production lines capacity optimization The ultimate goal is to create a digital twin of the factory for predictive and prescriptive analysis for a better decision-making. Your Role... Indeed, data science complemented with Machine Learning (ML) is increasingly used in industry and brings substantial benefits. However, the process to develop, deploy, evaluate and evolve them is more complex and less mastered than for traditional software. This implies that a substantial effort has to be produced for each new ML model/system, and impedes the adoption of this technology. You will contribute to research work in the area of data science and machine learning for Industry 4.0 factories . Such research concerns the development of theories, techniques and tools to ensure that the deployment of ML systems are secure, efficient and robust. More specifically, the topics that may be explored include (but are not limited to): Identifying and adapting data curation and sanitization techniques to the context of Industry 4.0 Comparing and complementing statistical models with ML ones Contributing to theories, techniques and tools to ensure the secure, efficient and robust deployment of ML systems Improving verification with traditional ML, but also deep learning Applying these techniques to severall Cebi use cases Publishing your research contribution in top-venues in the fields of software engineering and ML. The results of the project are expected to apply to multiple use cases. Depending on your profile, the project can focus more on theory, development and/or applications. However, all three aspects are expected to be covered during the project. The Supervision Team You Will Be Working With Is Dr. Maxime Cordy: daily advisor Prof. Yves Le Traon: head of SerVal You Will Be Required To Perform The Following Tasks Carrying out research in the predefined areas Survey the scientific literature in the relevant research domains Disseminating results through scientific publications Communicate and closely work with the partner to collect requirements and report results Implement proof-of-concept software tools Your Profile... Qualification: The candidate should possess a PhD degree (or equivalent) in Computer Science with strong programming skills. Experience : The ideal candidate should have some knowledge and/or experience in a number of the following topics: Software engineering Machine learning and AI Data science and statistics IoT and Industry 4.0 Strong software development skills are mandatory. Language Skills: Fluent written and verbal communication skills in English are required. Here’s what awaits you at SnT... Exciting infrastructures and unique labs. At SnT’s two campuses, our researchers can take a walk on the moon at the LunaLab, build a nanosatellite, or help make autonomous vehicles even better The right place for IMPACT. SnT researchers engage in demand-driven projects. Through our Partnership Programme, we work on projects with more than 45 industry partners Be part of a multicultural family . At SnT we have more than 60 nationalities. Throughout the year, we organise team-building events, networking activities and more Find out more about us! In Short... Contract Type: Fixed Term Contract 18 Month Work Hours: Full Time 40.0 Hours per Week Location: Kirchberg Job Reference: UOL04074 How to apply... Applications should include: Full CV, including list of publications and name (and email address, etc) of three referees Transcript of all modules and results from university-level courses taken Research statement and topics of particular interest to the candidate (300 words) Motivation letter All qualified individuals are encouraged to apply. Early application is highly encouraged, as the applications will be processed upon reception. Please apply ONLINE formally through the HR system. Applications by Email will not be considered. The University of Luxembourg embraces inclusion and diversity as key values. We are fully committed to removing any discriminatory barrier related to gender, and not only, in recruitment and career progression of our staff. About the University of Luxembourg... The University of Luxembourg aspires to be one of Europe’s most highly regarded universities with a distinctly international and interdisciplinary character . It fosters the cross-fertilisation of research and teaching , is relevant to its country, is known worldwide for its research and teaching in targeted areas, and is establishing itself as an innovative model for contemporary European Higher Education. The University`s core asset is its well-connected world-class academic staff which will attract the most motivated, talented and creative students and young researchers who will learn to enjoy taking up challenges and develop into visionary thinkers able to shape society. Further information For further information, please contact us at maxime.cordy@uni.lu or yves.letraon@uni.lu
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