Doctoral candidate (PhD student) in Computer systems for Machine Learning


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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!

The Interdisciplinary Centre for Security, Reliability and Trust (SnT) invites applications from highly motivated PhD candidates in the general area of software engineering within its SEDAN research group. SnT carries out interdisciplinary research in secure, reliable and trustworthy ICT systems and services, often in collaboration with industrial, governmental or international partners. For further information, you may refer to https://wwwen.uni.lu/snt

The SEDAN (SErvices and Data mANagement) research group, headed by Prof. Radu State addresses impact-oriented research activities in the areas of security, service management and monitoring. More specifically the group is interested on designing architectures, algorithms and approaches in the context of the new challenges given by ever increasing volumes of data, multiple and permanent connectivity and new distributed consensus systems based on blockchain paradigms. https://wwwen.uni.lu/snt/research/sedan

Your Role

This is a fully funded position for 3 years (extendable to an additional 4thyear) connected to a EuroHPC JU project called MAELSTROM about using machine learning to assist in weather prediction.

The MAELSTROM project is about supplementing traditional numerical simulation in weather prediction with alternate sources of data and using machine learning algorithms to augment the precision and accuracy. The task of SnT lies in primarily in modelling of computer systems to understand performance implications of using one architecture over another for the machine learning applications to be used.

The successful candidate will be supervised by Dr. Mats Brorsson (also Professor at KTH Royal Institute of technology) from the University of Luxembourg, and join a strong and motivated research team lead by Prof.  Radu State.

The position holder will be required to perform the following tasks:

  • Contribute to the project “MAELSTROM: MAchinE Learning for Scalable meTeoROlogy and cliMate”
  • Carry out research in the predefined areas
  • Disseminate results through scientific publications
  • Present results in well-known international conferences and workshops
Your Profile

Qualification: The candidate should possess a Master degree or equivalent in Computer Science, Computer engineering, or equivalent.

Experience: The ideal candidate needs to demonstrate knowledge and skills in one or more of the following topics:

  • Computer systems
  • Parallel programming
  • Performance modelling
  • GPU programming

The candidate must demonstrate strong analytical and programming skills.

Knowledge in machine learning would be considered an advantage.

We are looking for someone who is curiosity driven and who wants to constantly learn new things.

Language Skills: Fluent written and verbal communication skills in English 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!

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: 36 months fixed-term contract with a further possible 1-year extension if required
  • Work Hours: Full Time 40.0 Hours per Week
  • Employee and student status
  • Location: Kirchberg
  • Job Reference: UOL03647
Further Information

Application should include:

  • Full CV, including:
    • For each degree received or currently enrolled in, provide the degree, institution name, institution city and country, and date (or expected date) of graduation. Include the title and short summary of your final (Bachelor / Master) Thesis if you did one.
    • List of publications (if any)
    • Name, affiliation and contact details of three referees
  • Transcript of all modules and results from university-level courses taken
  • Cover letter with motivations and topics of particular interest to the candidate (approx. 1 page)

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. It`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 mats.brorsson@uni.lu or radu.state@uni.lu

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