PhD Position in Computer Science (University of Luxemburg)

Contract Type: Fixed Term Contract Duration: 36 Month About the SnT The University of Luxembourg is an international research university with a distinctly multilingual and interdisciplinary character. The Interdisciplinary Centre for Security, Reliability and Trust (SnT) at the University of Luxembourg is a leading international research and innovation centre in secure, reliable and trustworthy ICT systems and services. We play an instrumental role in Europe by fueling innovation through research partnerships with industry, boosting R&D investments leading to economic growth, and attracting highly qualified talent. We look for researchers from diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and ICT Services & Applications. This industrial PhD position is part of the “Autonomous systems for Land, Air and Space” (ATLAS) IPGB Programme co-funded by the FNR, SnT and a consortium of industrial partners and administrations, including Volvo Buses e-Bus Competence Center, Emile Weber, GomSpace, Gradel, IEE, Nexxtlab, Telindus and Ville de Luxembourg. For more information on the ATLAS IPBG Programme, see here: https://edu.lu/wwpy7 Your role The successful candidate will join the PCOG Research Group, led by Dr. Grégoire Danoy, in collaboration with the UBIX Research Group, led by Prof. Raphaël Frank. Thanks to the partnership with the Volvo e-Bus Competence Center the student will work with the latest technologies in the field of electrification, address real-world challenges and apply the findings in practice. Frequent training visits to Volvo headquarters in Gothenburg, Sweden, are foreseen. This PhD project addresses the question of the optimal setup on an electric bus, with primary focus on the battery and charging methods. The current lack of knowledge regarding energy consumption models has led to the prevalent but inefficient strategy of oversizing batteries, resulting in unnecessary costs and environmental externalities. The project aims to develop advanced learning mechanisms, using real-world data from electric bus fleets and applying federated learning to create energy consumption models that account for variable operating conditions, such as ambient temperature and door opening patterns. Additionally, it will explore how automation—both at the local (bus) and global (fleet) levels—can contribute to energy reduction, investigating whether isolated or system-level automation offers the greatest benefits. You will be required to perform the following tasks: Carrying out research in the predefined areas Disseminating results through scientific publications Communicate and interact with the partner’s team to collect requirements and report results Implement and open-source proof-of-concept software tools Collaborate with other researchers of the IPBG ATLAS programme For further information, please contact gregoire.danoy@uni.lu Your profile Qualification: The candidate should possess an MSc degree or equivalent in Computer Science or any related engineering discipline. Experience: The ideal candidate should have some knowledge and/or experience in several of the following topics: Optimisation and/or machine learning algorithms Distributed AI (e.g., swarm intelligence, federated learning) Data Analytics and Management Statistic models / processing / analysis Strong analytical and programming skills are required (Python and C/C++). Prior proven experience in data-driven innovation projects is an asset. Most importantly, you should be curiosity driven and willing to constantly learn new things! Language Skills: Fluent written and verbal communication skills in English are required. We offer Multilingual and international character. Modern institution with a personal atmosphere. Staff coming from 90 countries. Member of the “University of the Greater Region” (UniGR) A modern and dynamic university. High-quality equipment. Close ties to the business world and to the Luxembourg labour market. A unique urban site with excellent infrastructure A partner for society and industry. Cooperation with European institutions, innovative companies, the Financial Centre and with numerous non-academic partners such as ministries, local governments, associations, NGOs … But wait, there’s more! Complete picture of the perks we offer Discover our Partnership Programme How to apply Applications should include: Full CV, including: - For each degree received or currently enrolled in, the degree, institution name, city, and country, and date (or expected date) of graduation - Title and short summary of final thesis - List of publications (if any) - Name, affiliation, and contact details of at least two recommenders - If available, link to GitHub repository including completed open-source projects Transcript of all modules and results from university-level courses taken Cover letter with motivations and topics of particular interest to the candidate (500 words) 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. All qualified individuals are encouraged to apply. In line with our values, the University of Luxembourg promotes an inclusive culture. We encourage applications from individuals of all backgrounds and are dedicated to upholding equality and respect for our employees and students. General information: Contract Type: Fixed Term Contract 36 Month Work Hours: Full Time 40.0 Hours per Week Location: Kirchberg Campus Internal Title: Doctoral Researcher Job Reference: UOL06852 The yearly gross salary for every PhD at the UL is EUR 40952 (full time). If you apply for this position please say you saw it on Academicoxy

Contract Type:

Fixed Term Contract

Duration:

36 Month

About the SnT

The University of Luxembourg is an international research university with a distinctly multilingual and interdisciplinary character.

The Interdisciplinary Centre for Security, Reliability and Trust (SnT) at the University of Luxembourg is a leading international research and innovation centre in secure, reliable and trustworthy ICT systems and services.
We play an instrumental role in Europe by fueling innovation through research partnerships with industry, boosting R&D investments leading to economic growth, and attracting highly qualified talent. We look for researchers from diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and ICT Services & Applications.

This industrial PhD position is part of the “Autonomous systems for Land, Air and Space” (ATLAS) IPGB Programme co-funded by the FNR, SnT and a consortium of industrial partners and administrations, including Volvo Buses e-Bus Competence Center, Emile Weber, GomSpace, Gradel, IEE, Nexxtlab, Telindus and Ville de Luxembourg. For more information on the ATLAS IPBG Programme, see here: https://edu.lu/wwpy7

Your role

The successful candidate will join the PCOG Research Group, led by Dr. Grégoire Danoy, in collaboration with the UBIX Research Group, led by Prof. Raphaël Frank. Thanks to the partnership with the Volvo e-Bus Competence Center the student will work with the latest technologies in the field of electrification, address real-world challenges and apply the findings in practice. Frequent training visits to Volvo headquarters in Gothenburg, Sweden, are foreseen.

This PhD project addresses the question of the optimal setup on an electric bus, with primary focus on the battery and charging methods. The current lack of knowledge regarding energy consumption models has led to the prevalent but inefficient strategy of oversizing batteries, resulting in unnecessary costs and environmental externalities. The project aims to develop advanced learning mechanisms, using real-world data from electric bus fleets and applying federated learning to create energy consumption models that account for variable operating conditions, such as ambient temperature and door opening patterns. Additionally, it will explore how automation—both at the local (bus) and global (fleet) levels—can contribute to energy reduction, investigating whether isolated or system-level automation offers the greatest benefits.

You will be required to perform the following tasks:

Carrying out research in the predefined areas
Disseminating results through scientific publications
Communicate and interact with the partner’s team to collect requirements and report results
Implement and open-source proof-of-concept software tools
Collaborate with other researchers of the IPBG ATLAS programme

For further information, please contact gregoire.danoy@uni.lu

Your profile

Qualification: The candidate should possess an MSc degree or equivalent in Computer Science or any related engineering discipline.

Experience: The ideal candidate should have some knowledge and/or experience in several of the following topics:

Optimisation and/or machine learning algorithms
Distributed AI (e.g., swarm intelligence, federated learning)
Data Analytics and Management
Statistic models / processing / analysis

Strong analytical and programming skills are required (Python and C/C++). Prior proven experience in data-driven innovation projects is an asset. Most importantly, you should be curiosity driven and willing to constantly learn new things!

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

We offer

Multilingual and international character. Modern institution with a personal atmosphere. Staff coming from 90 countries. Member of the “University of the Greater Region” (UniGR)
A modern and dynamic university. High-quality equipment. Close ties to the business world and to the Luxembourg labour market. A unique urban site with excellent infrastructure
A partner for society and industry. Cooperation with European institutions, innovative companies, the Financial Centre and with numerous non-academic partners such as ministries, local governments, associations, NGOs …

But wait, there’s more!

How to apply

Applications should include:

Full CV, including:

- For each degree received or currently enrolled in, the degree, institution name, city, and country, and date (or expected date) of graduation
- Title and short summary of final thesis
- List of publications (if any)
- Name, affiliation, and contact details of at least two recommenders
- If available, link to GitHub repository including completed open-source projects
Transcript of all modules and results from university-level courses taken
Cover letter with motivations and topics of particular interest to the candidate (500 words)

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.

All qualified individuals are encouraged to apply. In line with our values, the University of Luxembourg promotes an inclusive culture. We encourage applications from individuals of all backgrounds and are dedicated to upholding equality and respect for our employees and students.

General information: