Description

We are creating an interdisciplinary cohort of PhD students and Postdoctoral Research Fellows to work across several institutions and topic areas to progress towards a global understanding for links between water infrastructure and aquatic ecosystems. The positions are offered by Cornell University (School of Civil and Environmental Engineering), the University of California, Santa Barbara (Environmental Studies Program/Bren School of the Environment), and the University of Maryland (Center for Global Sustainability) as part of an upcoming project that will develop a global, time-series dataset documenting the past and present evolution of riverine systems under human influence.

The project will reconstruct historical hydraulic infrastructure operations—including dams, wells, and diversions—at the global scale and quantify their influence on river discharge; assess the impacts of hydraulic infrastructure on sediment transport, water temperature, and biodiversity through time-varying indicators; characterize the uncertainty associated with all key variables in the dataset; and validate the dataset and explore policy implications in collaboration with regional partners worldwide.

Details for each available position are provided below, with roles tailored to one or more of the thematic areas outlined above. 

PhD Position (Cornell University)

About the research. Dr. Galelli’s Critical Infrastructure Systems Lab offers one PhD position in areas broadly related to the representation of human actions in global hydrologic models. Potential topics of research include (but are not limited to): (1) Estimating reservoir storage dynamics at the global scale using satellite observations, geospatial datasets, and data-driven modeling approaches, (2) Reconstructing groundwater pumping and irrigation activities worldwide through the integration of remote sensing, agricultural statistics, and process-based modeling, and (3) Integrating human water-use datasets into a global hydrologic model, with an emphasis on understanding how human decisions influence water availability, extremes, and long-term trends.

Qualifications. Applicants must hold a Bachelor’s and/or Master’s degree in engineering, environmental science, Earth sciences, applied mathematics, or a related field. A solid background in hydrology, statistics/probability, or optimization is desirable; some familiarity with remote-sensing data or geospatial analysis is an advantage. Candidates should have basic programming skills (preferably in Python), with additional experience in scientific computing or data analysis considered a plus. No applicant is expected to meet all criteria, but strong quantitative skills and motivation to learn are essential.

Terms of Appointment. The position includes full tuition fees and competitive compensation.

Application procedure. Applications should be submitted online, following the guidelines provided by Cornell University Graduate School. Questions can be directed to Dr. Stefano Galelli.

PostDoc Position (Cornell University)

Qualifications. We are looking for a candidate with a PhD degree (or completion expected within 3–4 months) in Civil/Environmental Engineering, Environmental Science, or a related field, preferably with expertise in large-scale catchment hydrology, remote sensing, or climate impact assessments. Candidates with interdisciplinary backgrounds are welcome, but strong data-analytics skills and solid knowledge of process-based numerical modelling tools are required. Robust modelling and programming abilities (e.g., Python) are essential prerequisites. Experience with VIC (or similar hydrologic models), GIS, and large-scale computing—particularly proficiency in Fortran and/or C/C++—is highly desirable. The candidate should be well organized, proactive, and able to work both independently and in a team. Evidence of innovative scientific results achieved during the PhD, strong communication skills, and a proficient command of oral and written English are important evaluation criteria.

Responsibilities. The Postdoctoral Fellow will lead the development and implementation of a global hydrologic model, including the integration of newly generated datasets describing human water-use activities (e.g., reservoir operations, groundwater pumping, irrigation). The candidate will be responsible for completing the scientific tasks assigned within the project, taking a leading role in preparing publications, and coordinating closely with the other researchers to ensure effective integration of the different work packages. In addition to these core responsibilities, the successful applicant is expected to contribute more broadly to the research activities of the group and to serve as an active, collaborative member of the project team, including providing occasional guidance to MSc and PhD students.

Terms of Appointment. The successful candidate will be offered a Postdoctoral Associate position for 12 months, with possibility of extension based on performance. The hiring rate of pay for the successful candidate will be determined considering a variety of criteria, including prior relevant work, qualifications, and unique applicable skills.

Application procedure. Applicants are to submit a cover letter, a detailed curriculum vitae that includes a list of publications, graduate transcript, and the names and contact information for at least three references. The successful applicant anticipated hire date is March/April 2026. Review of applications will begin immediately and will continue until the position is filled. Questions can be directed to Dr. Stefano Galelli.

1-2 Postdoctoral Positions in sediment transport, water temperature, and biodiversity modeling (UC Santa Barbara)

About the research: The River System Science & Sustainability (RS³) Lab at UC Santa Barbara seeks Postdoctoral Researchers to support the development of REAMS (River Ecosystem Assessment Models), a new global framework evaluating how water infrastructure and environmental change shape river ecosystem processes. Work will focus on generating time-varying global indicators describing physical and ecological change in river systems. For this hiring round, sediment continuity and geomorphic alteration will be among the highest priorities.
Possible research topics include: (1) Process-based modeling of sediment continuity and geomorphic alteration, including representation of multiple grain-size classes and mixed transport processes (see e.g., here, for examples); (2) Global indicators of river temperature, water quality, and biodiversity response to regulated flow and sediment regimes, depending on candidate expertise.

Researchers will collaborate with project partners to ensure consistent integration of physical, ecological, and human-influence datasets across the REAMS framework.

Qualifications: Applicants should hold (or about to receive) a PhD in geomorphology, hydrology, water resources engineering or management, aquatic ecology, or a related field. Strong quantitative skills and proven experience with numerical modeling and scientific programming (preferably R or Python) are essential. Expertise in sediment transport or fluvial geomorphology is highly desirable for this hiring round.

Candidates should demonstrate ability to develop numerical or statistical models and analyze large datasets; a record of scholarly publication is advantageous. Experience with remote sensing, geospatial analysis, or machine learning is considered a plus, as is experience working on regional-to-global scales. Strong communication skills and interest in working within a multi-institutional research team are important.

Responsibilities: The Postdoctoral Researcher will deliver scientific tasks assigned within the project’s work packages, tailored to their expertise. Responsibilities include developing and applying numerical and geospatial models, assembling and analyzing datasets, and contributing to global indicators within the REAMS framework. Additional duties include preparing peer-reviewed publications, presenting results at conferences, and collaborating with project partners. Postdoctoral Researchers are also expected to provide mentorship to students, contribute to coordination across work packages, and participate in the intellectual life of the RS³ Lab. Interest in supporting proposal development or small grant efforts is welcome.

Terms of Appointment: The position is a two-year appointment, with potential extension based on performance, project needs, and funding availability. Extensions may be prioritized for candidates interested in contributing across multiple components of the REAMS framework.
Salary follows UC Santa Barbara Postdoctoral Scholar scales and will be commensurate with experience. The position provides access to computational resources, opportunities for international collaboration, and support for conference travel and professional development.

Application procedure. Applicants are to submit a cover letter, a detailed curriculum vitae that includes a list of publications, graduate transcript, 1 or 2 key publications, and the names and contact information for at least three references. The anticipated hire date is March/April 2026. Review of applications will begin immediately and will continue until the position is filled. Questions can be directed to Dr. Rafael Schmitt.

1 Postdoctoral Position in global groundwater and water use modeling with uncertainty analysis (University of Maryland)

Overview. The University of Maryland’s (UMD’s) Center for Global Sustainability (CGS) is seeking a postdoctoral research associate to contribute to reanalysis and uncertainty analysis of the global hydrologic cycle. Led by Dr. Thomas B. Wild and Dr. Kamal Chowdhury, the postdoc will join a dynamic UMD-CGS team focused broadly on discovering how humans have shaped the global water cycle through the operation of hydraulic infrastructure, and characterizing the uncertainty in those human influences and its propagation. Possible research topics for the postdoc include: (1) Using Machine Learning (ML) methods to analyze the historical operation of global groundwater well infrastructure and integrating the outputs into a global hydrological model; (2) Estimating historical global patterns in surface water withdrawals from emerging sectors such as data centers and critical minerals and materials; (3) Developing ML-based stochastic resampling methods to bound uncertainty in reanalysis time series and analyze how it propagates across systems and scales.

The researcher will join a dynamic team at UMD-CGS that is tackling a diverse range of global sustainability challenges, and will collaborate closely across the project’s partner institutions to ensure tight integration across models and datasets.

Qualifications. Applicants should hold (or expect to hold soon) a PhD in civil/environmental engineering, hydrology, environmental science, or a related discipline. Desired qualifications also include:

• Technical experience: running, developing, and analyzing outputs from large scale hydrological models. Experience with groundwater specifically is highly desirable.
• Computational: programming (python, julia, fortran, c++), HPC, large data management.
• Methodological: machine learning, uncertainty and sensitivity analysis, statistics
• Communication and teamwork: successful candidates are expected to be highly motivated, have strong written and oral communication skills, and work effectively as part of a large interdisciplinary team.

Responsibilities. The postdoc will be responsible for producing models, data products, and publications focused on global groundwater extraction, while also contributing to the UMD-CGS team’s efforts in other areas, including emerging sources of water use and uncertainty analysis. In addition, the postdoc will coordinate effectively with researchers at the project’s other institutions (e.g., to integrate data on human water uses into a global hydrological model). The postdoc will be expected to follow best practices in data and software management. Finally, the postdoc will be expected to communicate findings effectively at various workshops and conferences.

Terms of Appointment. The successful candidate will be offered a Postdoctoral Research Associate position for 12 months, with possibility of extension based on performance. The hiring rate of pay for the successful candidate will be determined considering a variety of criteria, including prior relevant work, qualifications, and unique applicable skills.

Application procedure. Applicants are to submit a cover letter; a detailed curriculum vitae that includes a list of publications, datasets, and/or model development activities; and the names and contact information for at least three references. The successful applicant’s anticipated hire date is March-June 2026. Review of applications will begin immediately and will continue until the position is filled. Questions can be directed to Dr. Thomas B. Wild.

Dr. Stefano Galelli is a computational scientist working on the interaction between critical infrastructure systems and the natural environment. As a member of the MSD Community of Practice, he co-leads the Working Group on “AI for MSD Research”

Dr. Galelli is an Associate Professor in the School of Civil and Environmental Engineering at Cornell University, where he leads the Critical Infrastructure Systems (CIS) Lab. His career has spanned Europe, Asia, and North America. A graduate of Politecnico di Milano, Italy, he first established his career overseas in Singapore, where he worked as a Postdoctoral Research Fellow at the National University of Singapore and as a faculty member at the Singapore University of Technology and Design. After more than a decade in Asia, Dr. Galelli’s career brought him to North America. His research is currently supported by the NSF, DOE, USGS, Schmidt Sciences, and the World Bank.

Dr. Galelli’s work examines the co-evolution of river basins and interconnected infrastructure systems, identifies emerging vulnerabilities, and provides robust solutions that balance resilience and sustainability. One major research direction is the development of computational models
of human behavior and their integration into large-scale hydrologic models [1]. Recently, the CIS Lab released a dataset covering 1985–2023 monthly-to-weekly time series of reservoir storage for all large dams in mainland Southeast Asia. By synthesizing these data, it developed the first open-source hydrologic–water management model describing the impact of dam operations in the Mekong River Basin [2].

His second research theme is the development of computational frameworks that enable domain-specific models (e.g., water, energy) to interoperate through cosimulation, namely the composition of individual models to enable the global simulation of interconnected systems. This allows us to understand how dynamic interconnections shape systems’ response and vulnerabilities. In the Greater Mekong Subregion, for example, Dr. Galelli and his team demonstrated that the joint operation of the hydropower network and power grid enables the restoration of environmental flows to downstream wetlands, a global biodiversity hotspot [3]. The main challenge ahead lies in scaling these data, models, and frameworks to the continental and global scales. Learn more about Dr. Galelli’s CIS Lab on his website or connect with him on X.

Highlighted Articles:
[1] Galelli, S., Turner, S.W.D., Pokhrel, Y., Ng, J.Y., Castelletti, A., Bierkens, M., Pianosi, F., Biemans, H. (2025) Advancing the Representation of Human Actions in Large-Scale Hydrological Models: Challenges and Future Research Directions, Water Resources
Research, 61(7), e2024WR039486.
[2] Eldardiry, H., Mahto, S.S., Fatichi, S., Galelli, S. (2025) VIC-Res Mekong: An opensource hydrological-water management model for the Mekong River Basink, Environmental Modelling & Software, 193, 106603.
[3] Galelli, S., Dang, T.D., Ng, J.Y., Chowdhury, A.F.M.K., Arias, M.E. (2022) Opportunities to curb hydrological alterations via dam re-operation in the Mekong. Nature Sustainability, https://doi.org/10.1038/s41893-022-00971-z.

Acknowledgment of support from the U.S. Department of Energy, Office of Science, Office of Biological & Environmental Research (BER), Regional and Global Model Analysis (RGMA) component of the Earth and Environmental System Modeling (EESM) Program.

DOI: https://doi.org/10.1029/2025AV001716

Abstract

Simulating the Earth system is crucial for studying Earth’s climate and how it changes. Modeling approaches that simplify the Earth system while retaining key characteristics are important tools to advance understanding. The simplicity and flexibility of idealized models enables imaginative science and makes them powerful educational tools. Evolving scientific community needs and increasing model complexity, however, makes it challenging to maintain and support idealized configurations in cutting-edge Earth system modeling frameworks. We call on the scientific community to re-emphasize model hierarchies within these frameworks to aid in understanding the Earth system, advancing model development, and developing the future workforce.

Acknowledgment of support from the U.S. Department of Energy, Office of Science with compute resources from National Energy Research Scientific Computing Center (NERSC).

DOI: https://doi.org/10.1029/2024WR038928

Abstract

The National Water Model (NWM) is a key tool for flood forecasting, planning, and water management. Key challenges facing the NWM include calibration and parameter regionalization when confronted with big data. We present two novel versions of high-resolution (∼37 km²) differentiable models (a type of hybrid model): one with implicit, unit-hydrograph-style routing and another with explicit Muskingum-Cunge routing in the river network. The former predicts streamflow at basin outlets whereas the latter presents a discretized product that seamlessly covers rivers in the conterminous United States (CONUS). Both versions use neural networks to provide a multiscale parameterization and process-based equations to provide a structural backbone, which were trained simultaneously (“end-to-end”) on 2,807 basins across the CONUS and evaluated on 4,997 basins. Both versions show great potential to elevate future NWM performance for extensively calibrated as well as ungauged sites: the median daily Nash-Sutcliffe efficiency of all 4,997 basins is improved to around 0.68 from 0.48 of NWM3.0. As they resolve spatial heterogeneity, both versions greatly improved simulations in the western CONUS and also in the Prairie Pothole Region, a long-standing modeling challenge. The Muskingum-Cunge version further improved performance for basins >10,000 km². Overall, our results show how neural-network-based parameterizations can improve NWM performance for providing operational flood predictions while maintaining interpretability and multivariate outputs. The modeling system supports the Basic Model Interface (BMI), which allows seamless integration with the next-generation NWM. We also provide a CONUS-scale hydrologic data set for further evaluation and use.

Description

The Climate Modeling and Impacts Group and the Keller Research Group at Dartmouth College invite applications for a postdoctoral researcher with expertise in quantitative methods and research interests related to climate science.The successful candidate will be co-advised by Professors Justin Mankin (Geography) and Klaus Keller (Engineering) and become part of two collaborating transdisciplinary research groups.

The postdoctoral fellow will co-lead research to improve the characterization and understanding of heat driven mortality risks and the design of strategies to manage these risks. Qualified candidates will have a strong quantitative background in relevant disciplines (e.g., applied math, operations research, statistics, engineering, epidemiology, or Earth sciences). We especially value applicants who are highly motivated to collaborate across more than one discipline. The fellow will enjoy ample opportunities to co-design their project portfolios and for transdisciplinary research collaborations. The position provides unique opportunities for research, education, outreach, decision support, and professional development.

This position is full-time, non-remote, in-residence at Dartmouth in Hanover, NH, with start date as early as January 1, 2026. The initial appointment will be for a period of one year, with possibility of renewal for at least one additional year. The salary will be competitive, commensurate with experience.

Postdoctoral researchers are supported by the Guarini School for Graduate and Advanced Studies, including their community initiatives. Dartmouth as a whole is committed to academic excellence and encourages the open exchange of ideas within a culture of mutual respect. Dartmouth welcomes people with different backgrounds, life experiences, and perspectives and believes that diversity in all its forms enhances academic excellence. Applicants should address in their materials how their research, teaching, service, and/or life experiences prepare them to serve Dartmouth’s commitment to academic excellence in an environment that is welcoming to all.

Review of applications will begin immediately, and will continue until the position is filled. Recommendation letters will be requested only for finalists. For more information about the position, please contact Prof. Justin Mankin ([email protected]) and Klaus Keller ([email protected]).

Kendall Mongird is a Data Scientist at Pacific Northwest National Laboratory where she’s worked since 2017. She has a BSc. in Quantitative Economics from California Polytechnic State University and a MSc. in Economics from the University of Edinburgh. Kendall’s research focuses on geospatial analysis, modeling, and visualization and on identifying how dynamic geospatial constraints may impact energy systems in the future. Kendall enjoys developing open-source software and datasets and is the scientific lead for the Capacity Expansion Regional Feasibility (CERF) model

Kendall has led development of CERF, an open-source geospatial power plant siting model developed at Pacific Northwest National Laboratory, since 2021. CERF was developed to translate long-range energy planning capacity outputs into projected site-specific power plant locations. The model bridges the gap between regional planning and the spatial precision needed for electric grid operations modelling, land use analysis, and other impacts. Energy infrastructure decisions are deeply spatial. Siting depends not only how much capacity is needed, but on where development is even technically feasible and how it might interconnect to the electric grid. Operating at 1 km resolution, CERF incorporates key constraints such as land availability, slope, protected areas, population density, water availability, and natural hazard exposure. Kendall has applied CERF in various integrated modelling experiments to explore how the electricity system may evolve over time, ensuring that long-term energy planning models align with onthe-ground feasibility. This capability is increasingly important given the uncertainty in both long-term planning assumptions and changes in site-level geospatial constraints.

Building on CERF’s flexible framework, Kendall has recently developed a modeling extension that supports data center siting. As artificial intelligence and cloud computing continue to grow, the siting of large-scale data centers has become a multisectoral challenge, influenced by power demand, fiber connectivity, and physical siting constraints. The modeling extension leverages CERF’s high-resolution geospatial data and siting evaluation capabilities to determine where data centers may be built in the future. By evaluating potential siting patterns, Kendall and her colleagues explore how different data center growth scenarios may impact the electric grid and water systems under alternative futures.

Dr. Casey Burleyson is an Earth Scientist at Pacific Northwest National Laboratory where he’s worked since 2014. He has a B.S. in Meteorology and a Ph.D. in Atmospheric Sciences from North Carolina State University and a M.S. in Applied Physics from Columbia University. A meteorologist by training, Casey’s scientific work focuses on understanding how weather variability and extreme events impact energy systems. Casey is an advocate for open science and is the PI for the MultiSector Dynamics – Living, Intuitive, Value-adding, Environment (MSD-LIVE). MSD-LIVE is a collaborative open science platform for the MultiSector Dynamics community.

Casey led the brainstorming and development efforts for MSD-LIVE starting in 2019. The goal of the project is to leverage cutting-edge cloud technology to facilitate collaboration across the MSD community. As in many other communities, MSD researchers struggled with data and code management – from managing storage to making it easy for others to find and re-use data and code. However, the extraordinary diversity of MSD research, encapsulated in the “multi-” descriptor that applies to basically every aspect of MSD science, exacerbated these challenges. To meet the unique needs of the MSD community, Casey and his team developed MSD-LIVE – a cloud-based, flexible, and scalable data and advanced computing platform that enables MSD researchers to document and archive their data, run their models and analysis tools, and share their data, software, and multi-model workflows.

Built on the Amazon Web Services (AWS) cloud, MSD-LIVE is anchored around a centralized data repository that project teams can use to document, archive, and share their data. Since the v1 release of MSD-LIVE in August of 2022, 240 active users have used the platform to archive over 130 datasets covering topics spanning electricity infrastructure siting, water rights, and projections of electricity demand. MSD-LIVE datasets have been downloaded almost 1000 times since the start of 2024. MSDLIVE is also leveraging the cloud computing capabilities in AWS to host on-demand, interactive Jupyter notebooks to train new users to understand and run canonical MSD models like the Global Change Analysis Model (GCAM). During the GCAM annual meeting in 2024, MSD-LIVE supported nearly 150 people running components of the GCAM model in real-time on the AWS cloud. MSD-LIVE’s Jupyter notebooks have been used over 1700 times in the last year.

Casey loves the collaborative, community-oriented nature of the MSD-LIVE project and leading the team building the platform: “MSD-LIVE is a great example of technology meeting the moment. The extent to which the platform has been adopted by the community shows that the tools we’re building are solving real challenges faced by MSD researchers. All credit goes to the team of innovative, mission-focused software engineers building MSD-LIVE.”

About the Delta ISB

The Delta Independent Science Board (Delta ISB) and California Sea Grant are seeking a postdoctoral scholar to support the Delta ISB’s ongoing activities. The Delta ISB, consisting of 10 prominent scientists from across the United States, is charged with providing oversight of the scientific research, monitoring, and assessment programs that support adaptive management of the Sacramento-San Joaquin Delta – the hub of California’s water supply system. The Delta ISB also conducts reviews of specific documents or programs that are self-initiated or requested by the Delta Stewardship Council or other agencies, including review of the scientific basis for Delta Plan amendments, the Bay Delta Water Quality Control Plan, Delta conveyance, and more. The Delta ISB has produced influential reports on topics such as water quality, fish and flows, adaptive management, non-native species, water supply reliability, the monitoring enterprise, and food webs.

Position Description

The postdoctoral scholar, employed by the University of California, San Diego, will work directly with the Delta ISB to achieve its goals and responsibilities of providing reviews of the science supporting adaptive management in the Delta. Salary range will be $5,728.26 to $6,388.14 per month based on experience.

The Delta ISB is currently conducting reviews on critical topics important to management, including contaminants monitoring and decision-making under deep uncertainty. The postdoctoral researcher will explore the science and syntheses conducted on the topic in the Delta and other regions and help identify and describe the latest scientific approaches and emerging issues.

Specific responsibilities would include, but not be limited to:

1. Writing syntheses on issues and topics to inform Delta ISB reviews
2. Conducting literature reviews on key science topics
3. Conducting analyses of data and information gathered from workshops and surveys
4. Exploring emerging Delta issues
5. Engaging and interviewing agency personnel, scientists, community members, and other interested parties
6. Contributing to workshops and panels to inform reviews

In addition, there will be an opportunity to conduct independent research. Postdoctoral scholars will be expected to present at conferences and write peer-reviewed papers.

Qualifications

• A recent doctorate degree received within the last three years (after 9/2022) in a relevant discipline in the environmental sciences is required. A degree in (eco)toxicology, ecology, or chemistry is preferred.
• Must be based in the U.S.
• Must be able to work in an interdisciplinary team.
• Must have knowledge and experience transferring ecological and/or hydrologic concepts across systems.
• Proven resourcefulness when navigating complex systems or filling data gaps.
• Strong written and oral skills, with an ability to distill and present complex environmental topics to technical and general audiences.
• Experience or aptitude in interacting with policymakers, agencies, community groups, or the public.
• Ability to work independently, take initiative, and proactively develop creative solutions and drive project outcomes.

How to Apply

The position will start in late 2025/early 2026. Initial appointments will be for one year, with the potential to renew for one or two additional years based on experience for a maximum of three years. The position can be fully remote, with travel to in-person meetings and conferences. If space allows, the position can also be based at the Delta Stewardship Council in Sacramento, CA, or the office of California Sea Grant in La Jolla, CA. If interested, please submit the following items via eSeaGrant.

1. A cover letter with a statement of interest in the position and qualifications (2-page limit)
2. A curriculum vitae
3. Names/contact information for three references
4. A statement of research describing your relevant background/career goals (3-page limit)

Application review will start on 8/27/25. The position will remain open until it is filled. Applicants must create an eSeaGrant account to access the application portal. More information about the position can be found on the California Sea Grant’s web page.

Questions? Email [email protected] and [email protected].

Description

European and Canadian students who want to study at IHE Delft to prepare for pursuing careers at the crossroads of space and earth observation technology and water management are invited to apply for new scholarships offered by the European Space Agency (ESA) in collaboration with IHE Delft.

Two ESA scholarships

ESA will award two scholarships that cover the whole tuition fee for the 2025-2026  MSc Programme in Water and Sustainable Development starting in early November 2025. The scholarship programme enables students to deepen their academic expertise and prepare for careers in the water sector with a strong link to the relevant space and earth observation technologies, such as remote sensing and GIS.

The scholarship programme is open to students who are citizens of any of the 23 ESA Member States, the three ESA Associate Member States or Canada.

ESA is particularly interested in candidates who show clear motivation to work in the space sector, plan to focus their thesis on a space-related water topic and can benefit academically and professionally from the programme.

Eligibility

To be eligible for an ESA Academy Academic Scholarship, students must fulfil the following criteria at the start date of the academic programme:

• be minimum 18 years old at the time of the official start date of the academic programme; 
• own a nationality of Austria, Belgium, Czechia, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Luxembourg, The Netherlands, Norway, Poland, Portugal, Romania, Spain, Sweden, Switzerland, the United Kingdom, Slovenia, Slovakia, Latvia, Lithuania or Canada;
• not attend the academic programme as an incoming Erasmus student;
• not benefit of any additional financial aid to cover the tuition fees of the academic programme;
• agree with the conditions of the ESA Academy’s Privacy Policy;
• accept the guidelines of the ESA Academy Academic Scholarship;

Priority will be given to: 

• students who have not been sponsored by ESA before; 
• students who have less than 2 years of professional experience; 
• students who are expected to benefit more from the financial support;
• international students with diverse backgrounds and nationalities.

How to apply:

The deadline for applications is 15 June 2025. To apply for the ESA Academic Scholarship, you must first apply for academic admission to the MSc Programme. Once admitted, complete this form and submit it to: [email protected].

The decision by the Selection Committee will be communicated by 15 July 2025.

ESA is committed to achieving diversity and creating an inclusive environment. To this end, applications from all eligible candidates irrespective of gender, sexual orientation, ethnicity, beliefs, age, disability, social origin, or other characteristics are welcome.

Selection criteria

Note that ESA has the following selection recommendations:

• compliance with ESA eligibility criteria;
• interest in the space sector (student demonstrates motivation in performing a space related thesis)
• motivation to attend the academic programme;
• educational benefit of attending the academic programme;
• justification for, and expected benefit from, the financial support;
• academic merit.

Acknowledgment of support from the U.S. Department of Energy, a Framework for Improving Analysis and Modeling of Earth System and Intersectoral Dynamics at Regional Scales (HyperFACETS).

DOI: https://doi.org/10.1016/j.jhydrol.2025.133320

Abstract

Atmospheric forcings for hydrologic models often contain significant errors, but traditional modifications only employ bias correction or distributional transformations based on rainfall measurements. Deep learning could fuse multiple datasets for improved hydrologic modeling, but is difficult to interpret. Here we introduce a “differentiable” data fusion framework where a neural network is pre-trained to provide parameters a process-based hydrologic model while a second network is trained to weigh multiple forcings (Daymet, NLDAS, and Maurer) for a fused precipitation input to the combined model. The fused precipitation data greatly improved streamflow simulation performance (both low flow and high flow, but especially high flow). Applying adaptive weights to a single forcing did not yield improvements. Overall, the fusion placed a higher weight on Daymet, and slightly lower weights on NLDAS and Maurer. NLDAS’s weights increased in the humid eastern US while Maurer’s increased in mountainous regions. The fused precipitation had similar means and large-magnitude event performance to Daymet. However, it exhibited higher correlation with station-based precipitation than any individual forcing or their simple average, and had close to the smallest bias for large storms. Pre-training the parameterization network based on the best-performing single forcing (Daymet) yielded better results than those based on the average of forcings. Overall, the differentiable hydrologic model offers a generic hydrology-informed fusion method to improve streamflow prediction.