At a Glance
- Tasks: Join a team to develop and analyse soil moisture datasets using advanced modelling techniques.
- Company: Be part of the University of Southampton's School of Geography and Environmental Science, renowned for research excellence.
- Benefits: Enjoy flexible working hours, family-friendly policies, and opportunities for international collaboration.
- Other info: Full-time position until June 2028, with potential for extension; commitment to diversity and inclusion.
- Why this job: Contribute to impactful research on water-energy interactions while enhancing your skills in a supportive environment.
- Qualifications: PhD or nearing completion in relevant fields; strong quantitative and computational skills required.
The predicted salary is between 36000 - 60000 £ per year.
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 of equality, diversity and inclusion. The School is committed 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).
- Informal Enquiries: Please contact Prof. Justin Sheffield at justin.sheffield@soton.ac.uk.
Research Fellow in Hydrological Modelling and Data Assimilation in Southampton employer: University of Southampton
The University of Southampton offers an exceptional work environment for Research Fellows, particularly in the School of Geography and Environmental Science, where collaboration and innovation thrive. With a strong commitment to equality, diversity, and inclusion, employees benefit from flexible working arrangements and a supportive culture that encourages professional growth through engagement with international partners and cutting-edge research. This role not only provides the opportunity to contribute to impactful research on soil moisture variability but also fosters a community dedicated to advancing knowledge and addressing global challenges.
StudySmarter Expert Advice🤫
We think this is how you could land Research Fellow in Hydrological Modelling and Data Assimilation in Southampton
✨Tip Number 1
Familiarise yourself with the latest research in hydrological modelling and data assimilation. This will not only help you understand the project's objectives better but also allow you to engage in meaningful discussions during interviews, showcasing your knowledge and enthusiasm for the field.
✨Tip Number 2
Network with professionals in the field by attending relevant conferences or workshops. Engaging with experts can provide insights into current trends and challenges, and may even lead to valuable connections that could support your application.
✨Tip Number 3
Prepare to discuss your experience with high-performance computing environments and how you've applied quantitative skills in previous projects. Be ready to share specific examples that demonstrate your ability to handle complex datasets and contribute to the research goals.
✨Tip Number 4
Showcase your collaborative spirit by highlighting any past experiences working with stakeholders or interdisciplinary teams. Emphasising your ability to communicate effectively and work towards common goals will make you a more attractive candidate for this role.
We think you need these skills to ace Research Fellow in Hydrological Modelling and Data Assimilation in Southampton
Some tips for your application 🫡
Understand the Project:Familiarise yourself with the NERC-funded project and its objectives. Highlight your understanding of soil moisture variability and its implications in your application.
Tailor Your CV:Ensure your CV reflects your relevant experience, particularly in hydrological modelling, data assimilation, and any computational skills. Emphasise your PhD progress and any related research projects.
Craft a Strong Cover Letter:Write a compelling cover letter that connects your skills and experiences to the specific requirements of the role. Mention your quantitative skills and any relevant collaborations with stakeholders.
Prepare for Potential Interviews:Be ready to discuss your research experience and how it relates to the project. Prepare to explain your approach to problem-solving in hydrological contexts and your ability to work both independently and as part of a team.
How to prepare for a job interview at University of Southampton
✨Showcase Your Technical Skills
Make sure to highlight your quantitative and computational skills during the interview. Be prepared to discuss your experience with hydrological modelling, data assimilation, and any relevant software or programming languages you've used.
✨Demonstrate Your Research Experience
Discuss your previous research projects, especially those related to soil moisture variability or hydrological hazards. Be ready to explain how your work has contributed to understanding water-energy interactions and any outcomes that resulted from your research.
✨Engage with Stakeholder Collaboration
Since the role involves collaboration with stakeholders, share any past experiences where you worked with external partners. If you haven't had this experience yet, express your eagerness to learn and engage with stakeholders in future projects.
✨Prepare for Questions on Future Applications
Anticipate questions about how your research can benefit practical applications in sectors like agriculture and disaster risk management. Think of specific examples where improved soil moisture representation could enhance decision-making processes.
