Researcher in Explainable Artificial Intelligence for Environmental Applications
The successful candidate will join the “Environmental Research and Innovation” (ERIN) department. With a team of more than 190 scientists and engineers in life science, environmental science and IT science, the ERIN department tackles the major environmental challenges our society is facing today: climate change mitigation, ecosystem resilience, sustainable energy systems, efficient use of renewable resources, and environmental pollution prevention and control.
She/he will be part of ERIN’s Environmental Informatics Unit (ENVINFO), which designs, implements and evaluates innovative ICT methods and applications required to support the digital and environmental transition of our society and our economy.
Strategic interest for ERIN/Environmental Informatics Unit
In terms of Computer Science topics, the ENVINFO Unit focuses on Data Analytics (e.g. Artificial Intelligence, Machine Learning and Statistical Analysis) and on 2D/3D Interactive Visualisation (e.g. Visual Analytics, Augmented Reality and Geographical Information Systems).
The ENVINFO Unit cooperates with various environmental sciences experts to propose answers to some of the most critical socio-economic challenges of the 21st century, like managing sustainable resources, reducing the environmental impact of human activities or managing the consequences of extreme events.
A major trend currently observed in AI is to provide explainable models that the domain experts can understand and trust. This need is required in many circumstances, for instance, when the AI models are used to support actions in environmental crises (e.g. floods), to configure complex systems (e.g. bioreactors) or to decide on large investments (e.g. renewal of water or energy infrastructures). The question of the traceability and reproducibility of the processing of the data is also a relevant topic in this context. The ENVINFO Unit members have been working on understandable models for more than a decade but the recent impressive growth of the potential applications of AI in new fields requires the Unit’s capabilities to be strengthened in this domain.
The proposed position aims to extend our existing expertise in Artificial Intelligence and Machine Learning. We are looking for an R&T Associate to strengthen our capacities in making Artificial Intelligence more understandable.
The candidate should be passionate about opening “black box” models to understand how they work, how they are sensitive to the data used to build them and/or how they could exhibit unexpected behaviour in some special circumstances. She/he will also be asked to intervene in a variety of research tasks:
- Participate in RDI project development, in particular by contributing to scientific project proposal writing
- Actively contribute to the development of collaborative projects with industry, and put forward propositions in this regard
- Design (Explainable) AI algorithms and implement them in usable software components to be integrated into complex IT architectures
- Explore, develop and assess new applications of AI in the environmental domain (e.g. clean biotechnologies, water management, smart agriculture, environmental crisis management, etc.)
- Manage RDI project work packages
- Manage RDI projects (e.g. National Research Fund “CORE junior”, small service offers, etc.) as PI
- Identify and work on the development of future R&T and funding initiatives together with more senior staff
- Report internally and/or externally
- Be responsible for the realisation of deliverables in the expected time frame
Dissemination, valorisation and transfer:
- Disseminate, valorise and transfer RDI results (patents, licences, prototypes, publications, technical reports, conference participation)
- Produce scientific publications, including some as first author
- Write technical reports
- Make presentations at workshops
- Develop scientific and technological networks
Moreover the candidate should have expertise and an interest in designing and implementing innovative solutions to make the Machine Learning techniques used, for instance, in image processing, time-series analytics or predictive analytics, more explainable. Knowledge in using visualisation techniques to support the understanding of AI models is not required but will be considered a plus.
The selected candidate will be asked to apply her/his skills to research projects as well as to collaborative projects with industry. She or he must have a strong interest and proven experience in research (e.g. accepted publications) as well as in implementing software prototypes.
Some experience in contributing to writing project proposals targeting national or international calls is considered an asset.
International experience is considered an asset.
- A PhD in Computer Science, Data Sciences or equivalent
- Minimum 4 years of post-PhD RDI experience
- Knowledge of Luxembourg and the Luxembourgish socio-economic and industrial system is considered an asset
- Expertise in Artificial Intelligence, Machine Learning
- Experience in Time-Series Analytics, Signal Processing or Image Processing (theoretical knowledge and experience in related software tools and libraries)
- Software engineering (Agile methodologies)
- Interdisciplinary thinking, well-developed communication skills (oral and written) and team spirit to successfully integrate into the multicultural, multilingual and multidisciplinary work environment at LIST
- Experience in applying AI to environmental problems is considered a plus
- Knowledge in Data Visualisation or Visual Analytics is considered a plus
- Strong motivation-, challenge- and result-oriented mind-set
- Proficient spoken and written knowledge of English is mandatory
- Proficiency in at least one of the official languages of Luxembourg is an asset (French, German or Luxembourgish)
Candidates interested in the above position can apply online on our website www.list.lu.
The application file should include:
- A CV
- A motivation letter
- The names of two or three referees
- If possible, a list of publications, invited talks, patents, etc.