Doctoral position (PhD) on automated maintenance of machine-learning enabled systems

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.

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.

Machine Learning (ML) provides engineers with the prospect of producing data-driven software, with little manual code writing. We are at a turning point in the software industry, as key functionalities are no longer programmed in “the old fashioned way” but implemented by training ML models with data that reflect the expected system behaviour. This radical change offers a unique opportunity to further automate software production, subject to the condition that we can automatically maintain this combination of conventional code with ML models by developing accurate and actionable diagnosis and software update methods. One of the obstacle for adoption of machine-learning is the maintenance cost of the system after its deployment, hindering the benefit of machine-learning.

The overall research objective is the automation of the corrective maintenance activities for Machine-Learning (ML) enabled systems. Indeed, we ambition to define a clear-eyed and principled methodology to automatically validate and maintain data-intensive software systems, with limited human intervention. The main challenge is coping with the specificity of systems blending conventional code-base with ML components, to (almost) automatically detect, localize and fix the faulty behaviours over time.

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!

Your Role

You will contribute to research work in the area of applied machine-learning (ML) and software engineering (SE), with a special focus on the continuous and automated maintenance of machine-learning enabled systems. The topics that may be explored include (but are not limited to):

• Contributing to theories, techniques and tools to ensure the secure, efficient and robust deployment and evolution of ML systems
• Formalizing and devising fault detection and localization algorithms for Machine-Learning enabled systems, coping with the mix of ML models and code
• Formalizing and devising repair/fix actions to apply to machine-learning enabled systems
• Contributing to add your prototype algorithms in an open source MLops framework
• Applying your techniques to real-world use cases
• Publishing your research contribution in top-venues in the fields of ML and SE

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. You may be invited to apply your research on real-world use cases from one of our industry partners (STATEC, BGL BNP-Paribas, Lombard Int., Paypal…).

The Supervision Team You Will Be Working With Is
Prof. Yves Le Traon: head of SerVal research group

(https://scholar.google.com/citations?user=DmGlmNEAAAAJ&hl=en)

Dr. Maxime Cordy: daily advisor

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 in Computer Science.
Experience : The ideal candidate should have some knowledge and/or experience in a number of the following topics:
 

• Software engineering
• Machine learning and AI

Strong software development skills are mandatory. Interest in statistics and mathematics is welcome.

Language Skills: Fluent written and verbal communication skills in English or French are required.

Here’s what awaits you at SnT

• A stimulating learning environment. Here post-docs and professors outnumber PhD students. That translates into access and close collaborations with some of the brightest ICT researchers, giving you solid guidance
• 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
• Multiple funding sources for your ideas. The University supports researchers to acquire funding from national, European and private sources
• Competitive salary package. The University offers a 12 month-salary package, over six weeks of paid time off, health insurance and subsidised living and eating
• 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

But wait, there’s more!

• Complete picture of the perks we offer
• Discover our Partnership Programme
• Download the brochure: Why choose SnT for your PhD?

Students can take advantage of several opportunities for growth and career development, from free language classes to career resources and extracurricular activities.

In Short

• Contract Type: Fixed Term Contract 36 Month (extendable up to 48 months if required)
• Work Hours: Full Time 40.0 Hours per Week
• Start date: As soon as possible, before end of 2022
• Location: Kirchberg
• Employee and student status
• Job Reference: UOL04977

The yearly gross salary for every PhD at the UL is EUR 38.028,96 (full time)

Further Information

Applications should be submitted online and 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 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

University of Luxembourg is an international research university with a distinctly multilingual and interdisciplinary character. The University was founded in 2003 and counts more than 6,700 students and more than 2,000 employees from around the world. The University’s faculties and interdisciplinary centres focus on research in the areas of Computer Science and ICT Security, Materials Science, European and International Law, Finance and Financial Innovation, Education, Contemporary and Digital History. In addition, the University focuses on cross-disciplinary research in the areas of Data Modelling and Simulation as well as Health and System Biomedicine. Times Higher Education ranks the University of Luxembourg #3 worldwide for its “international outlook,” #20 in the Young University Ranking 2021 and among the top 250 universities worldwide.

Further information

For further information, please contact us at maxime.cordy@uni.lu or yves.letraon@uni.lu