Luxembourg Job Openings
Luxembourg Institute of Science and Technology (LIST)
E-2426 PHD IN USING EXPERIMENTAL DATA AND MACHINE LEARNING TO BENCHMARK HYDROLOGICAL MODELS
Esch-sur-Alzette
FULL TIME & CONTRACT
September 4, 2024
Ph D | up to 48 months (first initial contract of 14 months) | Belval
Are you passionate about research? So are we! Come and join us
The Luxembourg Institute of Science and Technology (LIST) is a Research and Technology Organization (RTO) active in the fields of materials, environment and IT. By transforming scientific knowledge into technologies, smart data and tools, LIST empowers citizens in their choices, public authorities in their decisions and businesses in their strategies.
How will you contribute?
During extreme hydrological conditions (floods and droughts), water fluxes can be regulated by processes that are difficult to observe during regular flow conditions. You will use over 20 years of data collected by a network of nested experimental catchments and existing process knowledge to test hydrological models and analyze water fluxes during extreme events across different geologies. By leveraging machine learning techniques, you will develop methods to highlight the limitations of conventional models during such extreme events. The objective is to evaluate and improve hydrological models, creating tools to reliably describe extreme events that shall ultimately contribute to improved risk management strategies.
The ‘Environmental Sensing and Modelling’ (ENVISION) unit is an interdisciplinary team of 45+ scientists, engineers, post-docs, and Ph D candidates – structured in three complementary groups focusing on agro-environmental systems research, remote sensing, natural resources modeling, and critical zone research.
Is Your profile described below? Are you our future colleague? Apply now!
You hold a Master’s degree in / environmental sciences / engineering / IT/ mathematics/ statistics
The candidate should be interested in the detailed investigation and modelling of hydrological extremes, and be able to carry out the following tasks:
- Calibrate and operate hydrological models using multi-disciplinary experimental data.
- Evaluate the performance of hydrological models in representing rare events.
- Develop and apply methods that leverage the advantages of machine learning and the physical understanding of experimental hydrology. Use these methods to benchmark existing hydrological models.
- Analyze water fluxes during extreme events and identify discrepancies with model predictions.
- Work with large datasets of multidisciplinary environmental observations.
- Test long-term changes in hydrological conditions and processes.
Dissemination, valorization and transfer
- Be an active part of the JCAR ATRACE community, participate in events, and develop collaborations.
- Disseminate your findings through scientific publications in peer-reviewed international journals and at conferences.
Training
- You will attend various trainings and courses at LIST and UNI.LU that will provide you with in-depth knowledge in your targeted field of expertise; training in research methods; academic writing and communication skills; a greater awareness of ethical issues in research; interdisciplinary expertise; and skills such as project management and presentation techniques.
- The various trainings will allow you to acquire ECTS credits (European Credit Transfer and Accumulation System). Throughout your Ph D project, you need to acquire 20 ECTS credits (1 ECTS equals approximately 25 working hours; this may include seminars, conferences, etc.).
Your LIST benefits
- An organization with a passion for impact and strong RDI partnerships in Luxembourg and Europe that works on responsible and independent research projects
- Sustainable by design, empowering our belief that we play an essential role in paving the way to a green society
- Innovative infrastructures and exceptional labs occupying more than 5,000 square metres, including innovations in all that we do
- An environment encouraging curiosity, innovation and entrepreneurship in all areas
- Personalized learning programme to foster our staff’s soft and technical skills
- Multicultural and international work environment with more than 50 nationalities represented in our workforce
- Diverse and inclusive work environment empowering our people to fulfil their personal and professional ambitions
- Gender-friendly environment with multiple actions to attract, develop and retain women in science
- 32 days’ paid annual leave, 11 public holidays, 13-month salary, statutory health insurance
- Flexible working hours, home working policy and access to lunch vouchers
Apply online
Your application must include:
- A motivation letter oriented towards the position and detailing your experience
- A scientific CV with contact details
- List of publications (and patents, if applicable)
- Contact details of 2 references
Please apply ONLINE formally through the HR system. Applications by email will not be considered.
Application procedure and conditions
We kindly request applicants to provide their nationality for statistical purposes only, as part of our commitment to promoting diversity and ensuring equal opportunities in our workforce. This information will be kept confidential and will not be used for any discriminatory purposes.
Please note that by applying you consent to share your application with Mr Christian VINCENOT, Associate professor in Engineering – Modelling and simulation of complex systems, from the University of Luxembourg.
Ph D additional conditions:
- Supervisor at UNI.LU: Prof Christian Vincenot
- Co-supervision at LIST: Dr. Davide Zoccatelli
- Co-supervisor at LIST: Prof. Laurent Pfister
- Work location: Luxembourg Institute of Science and Technology (LIST), Belvaux, Luxembourg
- Ph D enrolment: University of Luxembourg, Belval, Luxembourg
Candidates shall be available for starting their position in autumn 2024. Please note that university enrolment fees (currently 200 EUR per semester) must be covered by the successful applicant. Your master diploma has to be recognized in Luxembourg. Please refer to:
https://www.uni.lu/en/admissions/diploma-recognition/
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