Doctoral position (PhD) on robust and generalizable machine-learning software

University of Luxembourg

Luxembourg

June 10, 2022

Description

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.

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 STATEC (the national statistical institute of Luxembourg) and SnT.

Machine Learning (ML) provides engineers with the prospect of producing data-driven software, with little manual code writing. 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 robust and automated update methods.

The overall research objective is automating the robustification and generalization for Machine-Learning enabled systems. The main challenge is about leveraging and improving adversarial testing of ML, augmenting datasets with realistic yet adversarial cases, and generalizing the models.

In that perspective, the project is closely linked with STATEC needs, as it is investigating to what extent data science and machine learning could contribute to improve their internal processes and statistical analyses. The special case of large-size datasets, typically arising from high frequency automated recording of human activites, and the way to extract its statistical essence, is of high importance for the institute.

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

Your research may thus be applied to STATEC, and contribute to capacity building in data science (DS)/machine learning for official statistics.

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 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
  • Applying DS and ML techniques to topics of interest for STATEC
  • Publishing your research contribution in top-venues in the fields of ML and SE
  • The results of the project are expected to apply to multiple use cases, even if the main used case is related to mobile phone data. 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 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
  • Data science
  • Machine learning and AI
  • Strong software development skills are mandatory.

    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: asap, before end of 2022
  • Location: Kirchberg
  • Employee and student status
  • Job Reference: UOL04976
  • 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

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