The Interdisciplinary Centre for Security, Reliability and Trust (SnT) invites applications from PhD candidates in the general area of machine learning and Industry 4.0. SnT is carrying out interdisciplinary research in secure, reliable and trustworthy ICT systems and services, often in collaboration with industrial, governmental or international partners.
The Centre is rapidly expanding its research activities and is seeking highly motivated PhD candidates who wish to pursue research in close cooperation with our partners. For further information you may check: www.securityandtrust.lu and http://wwwen.uni.lu/snt/research/serval .
As the successful candidate, you will join the Security, Reasoning and Validation (SeRVal) group of the SnT, headed by Prof. Yves Le Traon. You will contribute more specifically to a partnership project with Ceratizit Luxembourg SARL, a worldwide leader in carbide product manufacturing. The topic of the project is “Automated Defect Recognition in Carbide Products” and it concerns the application of machine learning (in particular, image recognition) techniques and tools to detect defects in products manufactured by Ceratizit, at different stages of the fabrication process. The project also investigates scalable solutions to support the reliable deployment of related techniques (AutoML, image enhancement, data augmentation, feedback loops …) in the industrial settings of Ceratizit Luxembourg.
The project is held in close collaboration with Ceratizit and, as the successful candidate, you will be expected to spend an appreciable amount of your time in their Luxembourgish HQ and factory (located in Mamer).
The supervision team you will be working with is:
- Dr. Maxime Cordy: research scientist
- Dr. Jérémy Robert: research associate
- Prof. Yves Le Traon: head of SerVal
You will be required to perform the following tasks:
- Carrying out research in the predefined areas
- Disseminating results through scientific publications
- Participating in research project proposal drafting
- Assisting in the organization of relevant workshops
Qualification: The candidate should possess an MSc degree or equivalent in Computer Science, Applied Mathematics or Material Science (with good knowledge of computer science).
Experience: The ideal candidate should have some knowledge and/or experience in a number of the following topics:
- Machine learning
- Image recognition
- Data collection and storage pipeline
Strong programming skills are required (mainly python).
Language Skills: Fluent written and verbal communication skills in English are required.
The University offers a Ph.D. study program with an Initial contract of 14 months, renewable up to 36 months, with a further possible 1-year extension if required. The University offers highly competitive salaries and is an equal opportunity employer. You will work in an exciting international environment and will have the opportunity to participate in the development of a newly created university.
Application 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).
All qualified individuals are encouraged to apply.
Deadline for applications: February 28th, 2020. Early submission is encouraged, applications will be processed upon arrival (regardless of the desired starting date).