PHD IN USING EXPERIMENTAL DATA AND MACHINE LEARNING TO BENCHMARK HYDROLOGICAL ...(m/f)

PHD IN USING EXPERIMENTAL DATA AND MACHINE LEARNING TO BENCHMARK HYDROLOGICAL MODELS (m/f)

PhD | 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.

Do you want to know more about LIST? Check our website: https://www.list.lu/

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.

You will carry out your doctoral research project in the framework of the JCAR ATRACE project (https://jcar-atrace.eu). You will be part of a community of PhD students from multiple affiliate institutions, all working to reduce risk from extreme hydrological events in central Europe. In this context, you are expected to interact and collaborate with candidates from other partner institutions. Your work will be carried out under the co-supervision of LIST researchers and the University of Luxembourg. Throughout your PhD research project, you will be part of the Catchment and Eco-Hydrology research group at LIST and benefit from the multi-disciplinary expertise in hydrological sciences.

The ‘Environmental Sensing and Modelling' (ENVISION) unit is an interdisciplinary team of 45+ scientists, engineers, post-docs, and PhD candidates – structured in three complementary groups focusing on agro-environmental systems research, remote sensing, natural resources modeling, and critical zone research.

Embedded into the ENVISION unit, the ‘Catchment and eco-hydrology' (CAT) research group has its efforts geared towards a holistic understanding of intrinsically coupled hydrological and human systems. At the CAT group, we rely on our competencies in hydrology, geochemistry, sedimentology, and environmental systems engineering to gain a better understanding of eco-hydrological processes controlling hydrological and biogeochemical cycles, vegetation and sediment dynamics, pollutant removal, and ecosystem resilience.

You will hold a secondary affiliation with the Complex Systems Research Group (Team Nexus) at the University of Luxembourg, which will be responsible for awarding the PhD degree. Co-supervision from Team Nexus will complement the environmental expertise of LIST with advanced numerical skills.

The CAT group is seeking a highly motivated PhD candidate to work on the hydrological modeling of extreme events. This position is part of the JCAR ATRACE project, geared towards reducing flood and drought risk in Central Europe. Your research will leverage long experimental datasets for machine learning applications. A major goal consists in the identification of deficiencies proper to conventional hydrological models.

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:

Research work

• 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 PhD 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.

LIST is dedicated to maintaining an inclusive work environment and is an equal opportunity employer. We are committed to attracting, hiring, and retaining a diverse workforce. All applicants will be considered for employment without discrimination based on national origin, race, colour, gender, sexual orientation, gender identity, marital status, religion, age, or disability.

Applications will be continuously reviewed until the position is filled. An assessment committee will thoroughly evaluate applications, adhering to guidelines designed to ensure equal opportunities. The primary criteria for selection will be  [...]