The Youngflesh Lab in the Department of Biological Sciences at Clemson University is seeking 1-2 PhD students to join the lab in Fall 2026. The lab's research focuses on quantitative ecology, biodiversity conservation, and population biology, with a strong emphasis on using advanced data science tools such as hierarchical Bayesian modeling and AI to address questions in global change ecology. Potential research topics include drivers of biodiversity, demographic and life history dynamics, and ph...

The University of Bristol School of Mathematics is inviting applications for PhD positions in statistical and mathematical modelling, with a particular emphasis on infectious disease transmission. The program offers a wide range of research projects for the academic year 2025/26, supervised by leading academics in the fields of statistics, mathematics, and applied mathematics. Prospective students can explore topics such as statistical modelling of infectious diseases, mathematical biology, prob...

This fully funded PhD opportunity at Swansea University is offered by the National Centre for Suicide Prevention and Self-Harm Research, supported by Public Health Wales and Health and Care Research Wales. The project focuses on suicide prevention, self-harm, epidemiology, and public health, with a strong emphasis on using real-world data to understand suicide risk and self-harm across key populations. The research will utilize the SAIL Databank, one of the richest population-scale data sources,...

The National University of Singapore (NUS) Cities initiative is offering a fully funded PhD scholarship for outstanding candidates interested in research at the intersection of social science and city planning. Hosted within the NUS College of Design & Engineering, this interdisciplinary program brings together expertise from engineering, behavioural science, and urban studies. The PhD will be co-supervised by Dr. Prateek Bansal from the Department of Civil & Environmental Engineering and Profes...

The Department of Mathematics and Statistics at the University of Jyväskylä, Finland, invites applications for four to nine (4-9) Postdoctoral Researcher positions in Mathematics. These fixed-term positions, lasting 1–3 years, are set to begin mainly in fall 2026 or spring 2026, or as agreed. The roles are research-focused, with minimal teaching duties, and are ideal for promising researchers who have recently completed or are about to complete their doctoral degree in mathematics or a closely r...

The University of Copenhagen's Novo Nordisk Foundation Center for Basic Metabolic Research (CBMR) invites applications for postdoctoral fellowships in bioinformatics, single-cell omics, artificial intelligence, and systems biology. The Merino Group at CBMR is seeking a highly motivated postdoctoral researcher to join their interdisciplinary team, focusing on computational and integrative biology projects that aim to unravel the early molecular and regulatory changes preceding cardiometabolic dis...

This PhD project at the University of Leicester focuses on the genetic epidemiology of bronchiectasis, a chronic respiratory disease that has seen a significant rise in incidence and prevalence globally. Once considered rare, bronchiectasis is now recognised as the third most common chronic respiratory disease, highlighting the urgent need for advanced research into its genetic and epidemiological underpinnings. Hosted within the Department of Population Health Sciences, this research opportunit...

Project Overview: The project, "The Silent Threat in Breast Cancer: A Systems Biology Approach to Decoding Tumour Cell Dormancy and the Drivers of Metastasis," addresses a critical challenge in oncology: understanding why some breast cancer cells remain dormant for years before reactivating to cause incurable metastatic relapse. Despite advances in treatment, breast cancer remains the leading cause of cancer-related death for women in the UK, with late relapse posing a significant clinical probl...

This PhD project at The University of Manchester focuses on advancing artificial intelligence (AI) methods for learning from multi-modal spatio-temporal data, particularly in contexts where uncertainty, sparsity, and heterogeneity challenge traditional approaches. The research aims to develop unified, interpretable frameworks that integrate diverse data types—such as spatial-temporal trajectories, multi-variate time series, and contextual information—to generate reliable insights and predictions...