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- Tasks: Join a team to develop and analyse soil moisture datasets using advanced modelling techniques.
- Company: Be part of the University of Southampton, a leader in environmental science research.
- Benefits: Enjoy flexible working hours, family-friendly policies, and opportunities for international collaboration.
- Why this job: Contribute to impactful research on water-energy interactions and enhance decision-making in water resources.
- Qualifications: PhD or nearing completion, with skills in hydrological modelling, data assimilation, and machine learning.
- Other info: Full-time role until June 2028, with a commitment to diversity and inclusion.
The predicted salary is between 36000 - 60000 £ per year.
Organisation/Company UNIVERSITY OF SOUTHAMPTON Research Field Environmental science Geosciences Researcher Profile First Stage Researcher (R1) Application Deadline 2 Mar 2026 – 00:00 (UTC) Country United Kingdom Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No
Offer Description
We are seeking a highly motivated Research Fellow to join the Hydroclimatology Group at the University of Southampton, led by Professor Justin Sheffield.
You will lead the development and application of innovative Machine Learning (ML) frameworks to understand and predict the global hydrological cycle. The role will require bridging the gap between process-based physical modeling and scalable deep learning. You will contribute to several high-impact projects addressing hydrological extremes and their feedbacks within climate and human systems. Your work will have real-world impact, providing decision support for water-energy-food-health problems and enhancing early warning systems for global hazard risks.
The role will consist of:
- Methodological innovation: Develop cutting-edge ML models, including hybrid physics-informed approaches, to improve the estimation, monitoring and prediction of hydrological variables.
- Big data integration: Process and fuse multi-terabyte datasets, including satellite products, in-situ observations, and climate model ensembles.
- Process understanding: Develop and test hypotheses about the variability and interactions of hydrological processes across scales.
- Collaborative research: Work alongside national and international stakeholders to translate methodological innovations into understanding and tools that improve water resource management, sustainable development of water-energy-food systems, hazard early warning, and reduction of health and environmental impacts.
- Dissemination: Lead the preparation of high-impact manuscripts for peer-reviewed journals and present findings at international conferences.
Required qualifications and experience: To succeed, you will hold a PhD (or be close to completion) in Computer Science, Applied Mathematics/Statistics, Physics, Meteorology, Hydrology, or a related quantitative field. You will have technical expertise in one or more of the following:
- Advanced ML: Expertise in Deep Learning architectures, particularly those suited for spatiotemporal data (e.g., CNNs, LSTMs, Transformers, or Graph Neural Networks).
- Hybrid modeling: Experience with physics-informed machine learning or the integration of ML with data assimilation/multivariate statistics.
- Software frameworks: Excellent programming skills in Python, R or similar, with experience in frameworks such as PyTorch, TensorFlow, JAX, etc.
- HPC & Big Data: Proficiency in high-performance computing (HPC) environments and experience with geospatial libraries (e.g., Xarray, Dask).
Desired Experience:
- Prior experience with quantifying and understanding climate variability and extremes (floods, droughts, heatwaves, …).
- Knowledge of uncertainty quantification and probabilistic forecasting.
- Familiarity with sectors such as water resources systems, disaster risk mapping, agriculture, water-dependent energy systems, or ecosystem services.
About Us
This position is based in the School of Geography and Environmental Science. You will join a supportive, world-class research group within a University committed to fostering a culture ofequality, diversity and inclusion . The School iscommitted to providing equal opportunities for all and offer a range of family friendly policies,flexi-time and flexible working.We are a Disability Confident employer and the School holds a bronze Athena SWAN award.
Further Information
- Term: Full-time fixed term until 28 June 2028 (with potential for extension subject to funding).
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Research Fellow in Hydrological Modelling and Data Assimilation employer: Euraxess
Contact Detail:
Euraxess Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Fellow in Hydrological Modelling and Data Assimilation
✨Tip Number 1
Network with professionals in the field of hydrological modelling and data assimilation. Attend relevant conferences or workshops where you can meet researchers and academics, including those from the University of Southampton. Building these connections can provide insights into the role and may even lead to a recommendation.
✨Tip Number 2
Familiarise yourself with the latest research and methodologies in soil moisture variability and its applications. This will not only enhance your understanding but also allow you to engage in meaningful discussions during interviews, showcasing your passion and knowledge about the subject.
✨Tip Number 3
Consider reaching out to current or former researchers at the University of Southampton. They can provide valuable insights into the work culture, expectations, and the specifics of the project led by Professor Justin Sheffield, which can help you tailor your approach.
✨Tip Number 4
Prepare to discuss your experience with high-performance computing environments and any relevant projects you've worked on. Be ready to explain how your skills in hydrological modelling, satellite data assimilation, or machine learning can contribute to the goals of the research project.
We think you need these skills to ace Research Fellow in Hydrological Modelling and Data Assimilation
Some tips for your application 🫡
Understand the Role: Read the job description thoroughly to grasp the specific requirements and responsibilities of the Research Fellow position. Pay attention to the skills needed, such as hydrological modelling and data assimilation.
Tailor Your CV: Customise your CV to highlight relevant experience and skills that align with the job description. Emphasise your PhD work, quantitative skills, and any experience with stakeholders or related projects.
Craft a Compelling Cover Letter: Write a cover letter that clearly articulates your motivation for applying, your understanding of the project, and how your background makes you a suitable candidate. Mention specific experiences that relate to soil moisture variability and its applications.
Proofread and Edit: Before submitting your application, carefully proofread all documents for spelling and grammatical errors. Ensure that your writing is clear and professional, as this reflects your attention to detail and communication skills.
How to prepare for a job interview at Euraxess
✨Showcase Your Research Experience
Be prepared to discuss your previous research projects in detail, especially those related to hydrological modelling and data assimilation. Highlight any specific methodologies you used and the outcomes of your work.
✨Demonstrate Quantitative Skills
Since strong quantitative and computational skills are essential for this role, be ready to provide examples of how you've applied these skills in high-performance computing environments. Discuss any relevant software or programming languages you are proficient in.
✨Engage with Stakeholder Collaboration
If you have experience working with stakeholders, share specific examples of how you collaborated with them. If not, express your enthusiasm for gaining this experience and how you plan to approach stakeholder engagement in your research.
✨Prepare for Technical Questions
Expect technical questions related to soil moisture variability, water-energy interactions, and their implications. Brush up on recent advancements in these areas and be ready to discuss how they relate to the project’s goals.
