PhD Studentship: Developing Fair and Robust Cancer Risk Prediction Models Using Health Data
- Cambridge, United Kingdom
- Department of Public Health and Primary Care - Cardiovascular Epidemiology Unit
- Professor Angela Wood
Fully Funded PhD Studentship (Home Fees) Project Title: Developing Fair and Robust Cancer Risk Prediction Models Using Health Data Supervisor: Professor Angela Wood (Professor of Biostatistics and Health Data Science) Start date: January 2027 (or earlier) We are offering an exciting fully funded PhD studentship at the University of Cambridge, embedded within Cancer Data Driven Detection (CD3) - a major £10 million national research programme bringing together leading experts in cancer epidemiology, biostatistics, artificial intelligence, and health data science. THE PROJECT: Early cancer diagn
061/BI/2026 - Fellowship for Bachelors
- Oeiras, Portugal
- Agricultural sciences » Soil science
Instituto de Tecnologia Química e Biológica António Xavier Application for a Bachelor holder Fellowship within the ICJ25031 - IOVPoC-2025-01 Applications are invited for a Bachelor Holder Fellowship in in the scope of the project entitled “SaltShield: Halo-extremophile bioinoculants to reclaim agricultural saline soils” with the reference ICJ25031 - IOVPoC-2025-01, funded by InnoValley Proof-of-Concept Fund 4th Edition 2025 (Oeiras Valley PoC Award). Scientific Area: Agricultural Sciences. Academic degree: Bachelor degree in Biotechnology, or similar area. Other requisites to demonstrate: - Pr
PhD Geological Sciences: Mineralogical Controls on Redox Chemistry within the Subsurface
- Devon, United Kingdom
- School of Geography, Earth and Environmental Sciences (Faculty of Science and Engineering)
- Matt Bailey
Funding for: UK Students only. Due to funding restrictions, this studentship is only available to those candidates who meet the residency requirements for "Home" status. Funding amount: The studentship is supported for 3.5 years and includes full Home tuition fees plus a stipend of £21,805 per annum 2026-27 rate. DoS: Dr Matt Bailey ( matt.bailey@plymouth.ac.uk , tel.: 1752 584572) Applications are invited for a three and a half-year PhD studentship. The studentship will start on 1 st Jan 2027 Project Description Nuclear environmental safety demands a robust understanding of how radioactive ma
Fully Funded PhD Studentship: Microstructure and Defect Control in Recycled Aluminium Alloys
- Falmer, United Kingdom
- School of Engineering and Informatics
Project description The transition to a circular economy requires much greater use of recycled aluminium. However, wider adoption of secondary aluminium alloys remains limited by impurity-related microstructural defects and reduced casting reliability. Among these impurities, iron (Fe) is particularly problematic as it promotes the formation of Fe-rich intermetallic compounds, which can impair castability and reduce performance. At the same time, recycled alloys are often more susceptible to solidification defects during processing. This PhD project will investigate the interplay between grain
Research assistant in Culture and Communication
- Sweden
- Communication sciences
Malmö university is an open, innovative and international university that contributes to societal development thanks to its dedicated and experienced staff. Here, teachers, researchers, and other staff members with diverse skills work together to deliver education and conduct research of the highest quality. All professional categories and roles are important. We welcome you to apply for a job with us! Malmö University is a workplace and an educational institution that strives for an open and inclusive approach, where gender equality and equal opportunities add value to our operations. Here yo
PhD Studentship: Development of Innovative and Efficient Computational Fluid Dynamics Simulator based on Physics-Informed Neural Networks
- Manchester, United Kingdom
Despite significant advances in numerical techniques and computing hardware, the high computational cost of large-scale 3D computational fluid dynamics (CFD) modelling remains a major challenge. A new approach has emerged that integrates data and mathematical models through neural networks. This has led to the development of a method for solving partial differential equations (PDEs) known as physics-informed neural networks (PINNs). However, these approaches are still in their early stages of development and have yet to demonstrate their effectiveness for complex real engineering problems. Thi
PhD Studentship: An adaptive AI-driven Approach to Accessibility for Visual Impairments in Games
- Manchester, United Kingdom
Artificial intelligence is creating new opportunities to make games more accessible and inclusive for everyone. This PhD project will explore how AI can support players with visual impairments by enhancing understanding, navigation, and interaction within game worlds. Potential areas include dynamic guidance systems, adaptive game content, and personalised accessibility features that respond to players’ needs in real time. The successful candidate will work with an interdisciplinary supervisory team, benefiting from expertise in adaptive systems, accessibility and human-computer interaction, a
PhD Studentship - Vision Language Models for Micro-Expression Analysis
- Manchester, United Kingdom
Micro-expressions are tiny, involuntary facial movements that can occur when a person tries to hide an emotion, but are difficult to analyse because they are subtle, short-lived, and easily confused with ordinary facial movement. While many methods have been developed to recognise and localise micro-expressions, these results remain difficult to understand. The proposed models will be designed to identify where the relevant facial evidence occurs, describe what subtle change has been observed, and explain why a prediction has been made. The project will deliver new methods, benchmark protocols
PhD Studentship: Lightweight Trust-Aware Private Federated Learning for Secure UAV Swarms under Model Poisoning Attacks
- Manchester, United Kingdom
Unmanned Aerial Vehicle (UAV) swarms are becoming increasingly important for defence, emergency response, infrastructure inspection, and future autonomous systems. These swarms can use federated learning (FL), where multiple UAVs collaboratively train artificial intelligence models without sharing raw mission data. This supports privacy and efficiency, but it also creates a serious security risk: a compromised UAV may send poisoned model updates that corrupt the shared intelligence of the swarm. This PhD will develop lightweight, trust-aware methods to make FL models safer for UAV swarms. The
PhD Studentship: An adaptive AI-driven Approach to Accessibility for Visual Impairments in Games
- Manchester, United Kingdom
Artificial intelligence is creating new opportunities to make games more accessible and inclusive for everyone. This PhD project will explore how AI can support players with visual impairments by enhancing understanding, navigation, and interaction within game worlds. Potential areas include dynamic guidance systems, adaptive game content, and personalised accessibility features that respond to players’ needs in real time. The successful candidate will work with an interdisciplinary supervisory team, benefiting from expertise in adaptive systems, accessibility and human-computer interaction, a
PhD Studentship: AI-M Coast: AI-Modelling of Saltmarsh and Seagrass Vegetation for Coastal Protection
- Manchester, United Kingdom
Coastal flooding is becoming more frequent and severe due to climate change, rising sea levels, and increased storm intensity. Saltmarsh restoration, widely promoted as a nature-based solution, can reduce wave energy and flood risk while also supporting biodiversity and carbon storage. However, there is limited understanding of how effectively restored saltmarshes provide coastal protection compared with natural systems. This interdisciplinary project will combine laboratory experiments, numerical modelling, and advanced artificial intelligence (AI) techniques to improve predictions of the coa
Graduate Teaching Assistant - MCIS, Mathematics (Fall 2026 - Spring 2027)
- Jacksonville, United States
Department: Mathematical, Computing, and Informational Sciences Position Summary: A Graduate Teaching Assistant (GTA) in the Mathematical, Computing, and Informational Sciences – Mathematics department assists faculty by teaching lower-level courses or labs; developing teaching materials; and preparing and grading examinations, papers, or other student work. The GTAs must be assigned to and responsible for teaching a credit bearing course and will be under the supervision of a faculty member experienced in the teaching field. A GTA’s work with students will be closely supervised and must provi
Graduate Teaching Assistant - Biology Department (Fall 2026 - Spring 2027)
- Jacksonville, United States
Department: Biology Position Summary: A Graduate Teaching Assistant (GTA) under the supervision of the faculty and/or staff, may include assisting faculty with various lab related tasks, performing classroom instruction, as well as other academic support duties, and departmental operational needs, and other associated and clerical duties as assigned. Teaching schedule will vary dependent upon lab schedule, lab prep, in class lab time, and post lab work. Positions will be filled based on individual applicant’s skills, qualification, and departmental needs. If you choose to apply for employment
Graduate Teaching Assistant - Art & Design (Fall 2026-Spring 2027)
- Jacksonville, United States
Department: Art & Design Position Summary: The duties of the Graduate Teaching Assistant may include assisting with faculty with various lab related tasks, performing classroom instruction, as well as other academic support duties, and departmental operational needs, and other associated and clerical duties as assigned. Positions will be filled based on individual applicants’ skills, qualifications and departmental needs. Teaching schedule is dependent upon lab scheduling. If you choose to apply for employment as a graduate student at JSU, your transcripts and letters of recommendation will be
PhD Studentship: Development of Innovative and Efficient Computational Fluid Dynamics Simulator based on Physics-Informed Neural Networks
- Manchester, United Kingdom
Despite significant advances in numerical techniques and computing hardware, the high computational cost of large-scale 3D computational fluid dynamics (CFD) modelling remains a major challenge. A new approach has emerged that integrates data and mathematical models through neural networks. This has led to the development of a method for solving partial differential equations (PDEs) known as physics-informed neural networks (PINNs). However, these approaches are still in their early stages of development and have yet to demonstrate their effectiveness for complex real engineering problems. Thi
PhD Studentship: Automated, Explainable Geological Interpretation of 3D Digital Twins Under Conceptual Uncertainty
- Manchester, United Kingdom
Can AI learn to reason like a human - and recognise when it isn’t sure? This PhD tackles that challenge in a high-impact setting: interpreting 3D digital models of rock formations built from drone and laser-scan data. These models underpin decisions impacting net-zero ambitions, yet interpretation remains slow and subjective. We need tools that make geological reasoning faster, more transparent, and more consistent. Current AI systems struggle because they assume a single correct answer, when geological evidence often supports multiple plausible interpretations; so, training AI to copy one exp
PhD Studentship: Adaptive Large Language Models for Low-Resource Languages: Bridging the Global Digital Language Divide
- Manchester, United Kingdom
This PhD asks a different question: instead of demanding more data, can we build language models that learn smarter from less? You will design AI architectures that adapt to the structure of a language, including its grammar, script and complexity, rather than to how much text happens to be available online. You will test these ideas across a diverse range of underserved languages, and work directly with speaker communities to ensure the technology is genuinely useful to them. You will gain deep expertise in machine learning and natural language processing, access to high-performance computing
PhD Studentship - Universal Layered Triple-Route Architecture for Heterogeneous Quantum-Classical Security
- Manchester, United Kingdom
Quantum computers are on the horizon that could break the encryption protecting our banks, hospitals, and national infrastructure. This fully funded, part-time PhD studentship offers the chance to help build the next generation of communication security, before that threat arrives. You’ll develop ULTRA, a novel “Trinity” security framework that combines three independent forms of protection: a quantum channel, post-quantum mathematics, and traditional classical security, into a single, unified encryption key. Crucially, the system is expected to work with the infrastructure organisations alrea
PhD Studentship: Recovery of the Northern Pool Frog (Pelophylax lessonae): Habitat use and Population Ecology
- Salford, United Kingdom
- Dr. Robert Jehle
The studentship is with the University of Salford and the Amphibian and Reptile Conservation (ARC) Trust Academic Supervisor: Dr. Robert Jehle Academic Co-Supervisor: Dr. Victoria Franks Industrial Supervisors : Dr. John Baker, Jim Foster The studentship is fully funded and includes: • A fee waiver • A stipend of £22,852 pa for three years Final date for applications: 4 th October 2026 Interviews will be held October 2026 The candidate must be in a position to register by January 2027 Description: The northern pool frog ( Pelophylax lessonae ) is one of only four frog and toad species native t
PhD Studentship - Vision Language Models for Micro-Expression Analysis
- Manchester, United Kingdom
Micro-expressions are tiny, involuntary facial movements that can occur when a person tries to hide an emotion, but are difficult to analyse because they are subtle, short-lived, and easily confused with ordinary facial movement. While many methods have been developed to recognise and localise micro-expressions, these results remain difficult to understand. The proposed models will be designed to identify where the relevant facial evidence occurs, describe what subtle change has been observed, and explain why a prediction has been made. The project will deliver new methods, benchmark protocols