PhD in Testing Machine Learning Models and Self-Learning systems
Université du Luxembourg
Luxembourg, Luxembourg
il y a 7j

Your Role

Full time PhD students are intended to work on the STELLAR project. The subject of the thesis will be Definition and Measurement of Test Coverage Criteria in Machine-

Learning Models and Test Case Generation for Machine Learning Models based on Disagreement Discovery , which involve the development of effective techniques that can a) reliably measure and maintain the quality of training and test data that are used to build and evaluate ML models and b) generate test examples (similar to adversarial ones) that can improve confidence, identify issues and help securing the use of such ML models.

In particular the key attributes to be investigated regard the definition of appropriate test criteria and test data generation methods.

The successful PhD candidates will extensively explore and develop software engineering techniques that include the feasibility, practicality and success evaluation of prototype implementations

The team you will be working with :

  • Yves Le Traon : Primary advisor
  • Maxime Cordy : Co-advisor
  • Mike Papadakis : Co-advisor
  • Under the direction of a professor, the candidate will carry out research activities and write a thesis with the main goal of obtain a PhD in the area of Software Engineering.

  • This includes conducting literature surveys and establishing state-of-the-art; developing necessary experimental and simulation facilities where required;
  • planning, executing, and analyzing experiments and simulations; conducting joint and independent research activities; contributing to project deliverables, milestones, demonstrations, and meetings;
  • disseminating results at international scientific conferences / workshops and peer reviewed scientific publications.

    For further information, please contact us at michail.papadakis uni.lu, yves.letraon uni.lu

    Your Profile

  • Bachelor in Computer Science or related.
  • Master on a subject related to Informatics, or Software Engineering, or Computer Science, or Information Technology.
  • Strong background in program analysis and software engineering.
  • Strong programming and analytical skills.
  • Industry experience in information and communication technology will be considered as an advantage.
  • Commitment, team working, a critical mind, and motivation are skills that are more than welcome.
  • Optional : knowledge of machine learning, metaheuristics, statistics, and text analysis.
  • Language Skills : Fluent written and verbal communication skills in English are required.

    We offer

    The University offers a Ph.D. study program with a Fixed Term Contract up to 4 years in total, pending satisfaction of progress milestones (CDD), on full time basis (40hrs / week).

    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.

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