Each month, we provide up to £2,000 in grant money to early career researchers in quantitative disciplines.
Our aim is to support and assist PhD students and postdocs conducting research, particularly with costs that may be difficult to get funding for elsewhere, for example, travel for those who are caring for children, or expenses for volunteer work related to research.
Learn more about our grant programme terms and conditions.
Read on to hear from our latest winners, their research and how our grants will aid their work.
December grant winners
Natalia Wong (University of Oxford)
“I am a PhD candidate in the HDRUK-Turing Wellcome PhD programme in Health Data Science at the University of Oxford. My research centres around adapting and bridging AI models for healthcare, specifically deep risk prediction models for multimorbidity, using data from Electronic Health Records.
“I am honoured to receive the G-Research grant, which will support my participation in the NLDL conference and winter school. This conference includes a day with a significant portion dedicated to deep learning in health, aligning closely with my research focus. At the winter school, I look forward to sharing my work through a poster presentation and deepening my technical expertise to further strengthen my multidisciplinary research.”
Fabio Feser (Imperial College London)
“I am a Statistics PhD student at Imperial College London. My research focuses on method development in the field of high-dimensional statistics, blending a theoretical approach with practical considerations. In particular, I am actively developing a new penalised regression approach which provides joint variable and group false discovery rate control.
“The grant by G-Research will enable a research visit to Professor Chiara Sabatti’s lab at Stanford University, where I will be investigating Knockoffs, a new variable selection approach with false discovery rate properties and applications in genetics.”
Elisa Bergas Masso (Universitat Politècnica de Catalunya)
“I am a final-year PhD student in Environmental Engineering at the Universitat Politècnica de Catalunya, conducting research at the Barcelona Supercomputing Centre. My work focuses on modeling complex Earth system interactions, particularly the iron cycle and its role in global climate.
“This grant will support my first fieldwork experience as part of the 8th ESA Ocean Training Course, where I will observe atmosphere-ocean interactions firsthand. This experience will complement my computational expertise and contribute to my goal of improving Earth system models.”
Isabel Amaya Rodríguez (University of Seville)
“I am a Health Engineer (Biomedical Engineer) with extensive experience in data science, software development and AI. I work at Fundación Progreso y Salud, a non-profit research organisation under the Consejería de Salud y Consumo of the Junta de Andalucía. Here I manage healthcare data and develop AI models to address complex medical challenges.
“The G-Research grant will enable me to present my recent work, ‘A Multimodal Approach for Predicting Adverse Complications in Cardiopulmonary Bypass Surgeries‘, at NLDL 2025. This platform will provide an invaluable opportunity to share my findings and collaborate with leading experts in the field. I am sincerely grateful for this support, which will further propel my efforts at the intersection of artificial intelligence, healthcare and societal impact.”
Marisa Wodrich (Technical University of Denmark)
“I am a PhD student at DTU working on uncertainty quantification in deep learning. My research focuses on developing methods to increase the trustworthiness of machine learning models.
“This grant will enable me to attend the NLDL conference and winter school in Tromsø. I will use this opportunity to deepen my knowledge in uncertainty and responsible AI, as well as to engage with other researchers from my field.”
Lucas Arenstein (University of Copenhagen)
“I’m a PhD student at the University of Copenhagen. My research focuses on developing and analysing quantum-inspired algorithms based on tensor networks to solve differential equations.
“This grant will support my participation in the Northern Lights Deep Learning conference. I will present my latest work on integrating data into the quantized tensor train (QTT) framework for solving partial differential equations.”
Nicola Rimella (University of Turin)
“I am a PhD candidate in Civil and Environmental Engineering at the Polytechnic University of Turin, Italy. My research focuses on leveraging advanced technologies such as point clouds, digital models and machine learning to enhance the maintenance of road tunnels.
“The G-Research grant is providing essential support for my research stay at the University of Tokyo, enabling the development and validation of innovative solutions to advance this critical field.”
Congratulations to all of our grant winners.
