The Interdisciplinary Centre for Security, Reliability and Trust (SnT) invites applications from highly motivated PhD candidates in the area of Applied Artificial Intelligence within its SIGCOM research group. SnT plays 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 talents. SnT is home to students, researchers and faculty members from around the world. For further information, you may refer to www.securityandtrust.lu
The SIGCOM research group, headed by Prof. Symeon Chatzinotas, carries out research activities in the telecommunication and networking systems and services, including artificial intelligence applications and non-terrestrial networks, and is currently expanding its research activities in exploring several emerging technological trends. For more details, you may refer to the following: https://wwwen.uni.lu/snt/research/sigcom
We are looking for people driven by excellence, excited about innovation, and looking to make a difference. If this sounds like you, you have come to the right place!
The successful candidate will work with an academic supervisor from the University of Luxembourg in developing AI-based financial algorithms/solutions incorporate satellite datasets for investment management, and will join a strong and collaborative research team lead by Prof. Symeon Chatzinotas. Specifically, this is a fully funded position for 3 years (extendable to an additional 4th year) within a multidisciplinary national research project (FinSAT: Automated Investment Advice using Artificial Intelligence on Satellite Data). The project goals are to analyze various satellite and socioeconomic datasets to construct AI learning models that predict the markets’ directions with interpretable decision logic that can support asset management strategies.
The position holder will be required to perform the following tasks:
- Develop models and algorithms (Artificial Intelligence, Machine Learning, etc.) for the finance application area
- Work closely with project’s stakeholders from both technical and financial backgrounds
- Collect and refine structured and unstructured data from our sources
- Carry out research in the predefined areas
- Disseminate results through scientific publications
- Present results in well-known international conferences and workshops
The candidate should possess a master degree or equivalent in Computer Science/Engineering, Information Systems (Engineering), Telecommunication Engineering, Electrical Engineering, Mathematics, Applied Physics, or a relevant field.
The ideal candidate should have some knowledge and experience in a number of the following topics:
- Machine Learning techniques (e.g. clustering, deep learning, reinforcement learning)
- Knowledge on traffic congestion prediction, demand forecasting or financial forecasting models would be a plus
- A prior course in the fundamentals of statistics and probability is desirable
- Open source programming languages for large scale data analysis and deep learning frameworks such as Pytorch and Tensorflow
- Background in general wireless communications is highly desirable but not mandatory
- Good oral presentation skills: The candidate will be required to present and defend his/her work in front of wide audience of experts
Programming skills: Python, MATLAB, or C++
Language Skills: Excellent 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!
- 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.
- Contract Type: Fixed Term Contract 36 Month (extendable up to 48 months if required)
- Work Hours: Full Time 40.0 Hours per Week
- Location: Kirchberg
- Employee and student status
- Job Reference: UOL04928
The yearly gross salary for every PhD at the UL is 38 028,96 € (full time)
Applications should be submitted online and 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)
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.