PhD Position in Veterinary Medicine – Fully Funded at University of Cambridge
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The PhD in Veterinary Medicine at the University of Cambridge in Cambridge, United Kingdom, is a fully funded doctoral research programme designed for graduates in biological sciences, clinical sciences, veterinary medicine, and related disciplines. Offered through the Department of Veterinary Medicine, the programme provides access to advanced research facilities, specialist laboratories, clinical patient groups, and strong collaborations with leading research institutes within the university.
Programme Overview
This PhD by research is completed over a minimum of three and a maximum of four years full-time, including a one-year probationary period. Each doctoral candidate is assigned a primary supervisor, who may appoint an advisor or supervisory team to provide additional academic guidance.
The department has established research strengths in disease dynamics, infection and immunity, and systems pathology. Students may undertake clinical research, laboratory-based investigations, field studies, or computational biology projects. Some projects may involve research conducted abroad or in collaboration with external institutes. Depending on the funding body, certain students may complete laboratory rotations during the first year.
At the end of the first year, students must submit a written report and pass a formal viva assessment to progress from probationary status to full PhD registration. A progress report is also required at the end of the second year. The final examination consists of submitting a doctoral thesis and completing a viva voce examination.
Research Environment and Training
The PhD in Veterinary Medicine is entirely research-based, with no formal taught coursework. However, students may attend relevant specialist training sessions in consultation with their supervisor. All doctoral researchers participate in the Postgraduate School of Life Sciences Researcher Development Programme, which provides professional skills training, research ethics education, and career development support.
Students are expected to engage actively in departmental seminars, journal clubs, and research days. A literature review is recommended within the first four months and forms part of the first-year assessment. Doctoral candidates present their work at departmental seminars and participate in biannual research days through poster presentations or short oral talks.
Supervision and Feedback
Each student receives close academic supervision tailored to their project and research progress. Formal supervision hours vary depending on the project and stage of study. Students receive structured online feedback reports once per term and detailed feedback following the first-year assessment. Informal guidance and mentoring are provided throughout the programme.
Assessment Structure
The doctoral thesis must not exceed 60,000 words, excluding tables, figures, appendices, and bibliography. In exceptional cases, a limit of 80,000 words may be permitted with special approval. The thesis is examined in a viva voce examination conducted by one internal and one external examiner.
Academic Entry Requirements
Applicants should hold a UK Good 2:1 Honours degree or international equivalent. Suitable backgrounds include biological sciences, clinical sciences, veterinary medicine, mathematics, computer science, or related disciplines. A master’s degree may strengthen an application.
International applicants must meet English language requirements such as:
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IELTS Academic overall score of 7.0
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TOEFL iBT score of 100
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C1 Advanced or C2 Proficiency with specified minimum grades
Students requiring a UK visa must obtain an ATAS certificate after receiving an official offer.
Funding and Financial Information
Funding opportunities include research council support from BBSRC, MRC, the Wellcome Trust, university scholarships, and international funding bodies. Some supervisors may hold grant funding to support PhD students. Self-funded applicants are also eligible to apply.
Estimated annual costs for Home students include:
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University Composition Fee: £10,878
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Maintenance: £19,860
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Total estimated annual commitment: £30,738
Part-time study fees are calculated as a percentage of the full-time fee over an extended study period.
Application Process
Applications are submitted through the University of Cambridge Applicant Portal. Admissions operate on a rolling basis.
Applicants must identify and secure a suitable supervisor before applying. Only candidates who meet the minimum academic criteria and have a willing supervisor in place will be invited to interview. Interviews typically take place within one month of receiving a complete application, with decisions communicated shortly afterward.
A complete application requires:
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Two referees
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Academic transcripts
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CV or resume
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Evidence of English proficiency (if required)
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Research proposal
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Confirmation of proposed supervisor
Applicants may also apply for competitive awards such as the Gates Cambridge Scholarship, which requires additional documentation.
Security and Compliance
Offers of admission may be subject to security checks, particularly for research involving live animals, sensitive information, dangerous pathogens, or regulated laboratory environments. Where necessary, the university ensures that applicants are not unfairly disadvantaged during the clearance process.
How to Find a Supervisor
Prospective applicants must review the department’s research areas and contact potential supervisors whose expertise aligns with their interests. Initial contact should include a summary of research experience, proposed project ideas, funding information, and a CV. Applications without a confirmed supervisor cannot proceed to the interview stage.
The PhD in Veterinary Medicine at the University of Cambridge offers world-class research facilities, expert supervision, and strong links to clinical and biomedical research, making it a highly competitive and prestigious doctoral programme in veterinary and biomedical sciences in the United Kingdom.
Linköping University PhD 2026 in AI for Medical Imaging
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If you are planning to pursue a PhD in Europe at the intersection of artificial intelligence and healthcare, the opportunity at Linköping University is a strong choice. This fully funded PhD focuses on deep learning for medical imaging, with real-world applications in early lung cancer detection.
PhD Position Overview
University: Linköping University
Location: Linköping
Department: Biomedical Engineering
Supervisor: Anders Eklund
Program: Data-Driven Life Science (DDLS)
Degree Level: PhD
Duration: 4–5 Years
Deadline: May 14, 2026
Research Focus
This PhD is part of Sweden’s national Data-Driven Life Science (DDLS) initiative, aimed at advancing AI-driven biomedical research.
The project focuses on:
Deep learning for medical image analysis
Early detection of lung cancer
Combining:
High-resolution CT scan data
Clinical variables (age, smoking status, etc.)
Classifying lung nodules as benign or malignant
The research uses large-scale datasets (30,000+ subjects) and aims to improve diagnostic accuracy in healthcare systems.
Key Research Areas
Computer vision for medical imaging
Deep learning model development
Multi-modal data fusion (imaging + clinical data)
Large-scale biomedical data analysis
AI applications in precision medicine and diagnostics
Scholarship Benefits
The PhD position offers:
Starting salary of SEK 36,400/month (increases annually)
Fully funded PhD training (no tuition fees)
Access to advanced AI infrastructure, including:
High-performance computing systems
Participation in a national research program (DDLS)
Collaboration with:
Hospitals
AI research labs
Opportunities for teaching (up to 20%)
Eligibility Criteria
Applicants must meet the following requirements:
Master’s degree in:
Biomedical Engineering
Computer Science
Machine Learning
Electrical Engineering
Statistics or related fields
Strong background in:
Deep learning
Computer vision
Mathematics
Programming skills (especially Python)
English language proficiency
Preferred qualifications:
Experience in medical image analysis
Knowledge of large-scale data processing
Responsibilities
Selected candidates will:
Develop AI models for lung cancer detection
Analyze large medical imaging datasets
Collaborate with clinicians and researchers
Publish research in scientific journals
Participate in academic discussions and research meetings
Research Environment
Linköping University is one of Sweden’s leading institutions in AI and engineering, with strong links to national initiatives such as:
DDLS (Data-Driven Life Science)
WASP (AI research program)
ELLIIT (IT and mobile communication research)
The research group collaborates closely with hospitals and international partners, providing a highly interdisciplinary environment.
Application Process
To apply, candidates must:
Submit an online application before the deadline
Include academic transcripts and CV
Provide proof of qualifications and experience
Late or incomplete applications will not be considered.
Why Study in Sweden?
Sweden offers:
High-quality research and education
Strong focus on innovation and AI
Excellent work-life balance
International and inclusive academic culture
Final Thoughts
This PhD in Biomedical Engineering is ideal for candidates interested in AI, healthcare, and real-world impact. With access to large datasets, advanced computing resources, and interdisciplinary collaboration, it provides an excellent platform for building a career in medical AI research.
University of Stavanger PhD 2026 in Energy Engineering
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If you are planning to pursue a fully funded PhD in sustainable energy, the opportunity at University of Stavanger offers an excellent pathway into advanced research in geothermal systems. This PhD fellowship focuses on optimizing energy transfer in shallow geothermal wells, combining experimental work, modeling, and AI-driven optimization.
PhD Position Overview
University: University of Stavanger
Location: Stavanger
Department: Energy and Petroleum Engineering
Supervisor: Kristian Gjerstad
Degree Level: PhD
Start Date: August 2026
Duration: 3 Years
Deadline: May 30, 2026
Research Focus
This PhD project explores efficient and sustainable geothermal energy systems, aiming to improve heating and cooling technologies.
Key research objectives include:
Optimizing energy transfer in shallow geothermal wells
Reducing energy losses in circulation systems
Improving cost efficiency per kWh
Developing thermal and hydraulic models
Applying AI-based and hybrid optimization methods
Key Research Questions
How does well design affect heat transfer and energy losses?
What operating conditions maximize energy output?
How can models better predict geothermal system performance?
Research Tasks
The selected candidate will work on:
Experimental studies on heat transfer and pressure loss
Building and modifying flow loop systems
Developing computational thermal and hydraulic models
Applying AI and control algorithms for system optimization
Validating models using real-world data
Expected Outcomes
The project aims to deliver:
Advanced models for geothermal system design
Improved energy efficiency and sustainability
Practical solutions for future green energy systems
Scholarship Benefits
This fully funded PhD includes:
Annual salary of NOK 550,800
Pension and insurance benefits
Access to Norway’s public healthcare system
Paid parental leave and social benefits
Free Norwegian language courses
Relocation support
Access to sports facilities and wellness services
Eligibility Criteria
Applicants must meet the following requirements:
Master’s degree in:
Energy Engineering
Physics
Computer Science
Petroleum Engineering or related fields
Strong academic record (minimum grade equivalent to B)
Skills in:
Numerical modeling
Data analysis or AI
Experience in:
Experimental work (preferred)
Software development
Strong English proficiency
English Language Requirements
Applicants must provide one of the following:
TOEFL (minimum 90)
IELTS (minimum 6.5)
Cambridge CAE/CPE
PTE Academic (minimum 62)
Exemptions apply for candidates with prior education in English-speaking countries or EU/EEA programs.
Application Requirements
To apply, candidates must submit:
CV and academic records
Motivation letter
Research proposal (mandatory)
Certificates and diplomas
Proof of English proficiency
Relevant publications (if available)
Applications must be submitted through the official online portal.
Why Choose Stavanger?
Stavanger is a leading energy hub in Europe, making it an ideal location for research in sustainable technologies. The University of Stavanger is known for:
Strong industry collaboration in energy sectors
Focus on green transition and sustainability
International research environment
High quality of life and work-life balance
Final Thoughts
This PhD fellowship is ideal for candidates interested in renewable energy, AI-driven optimization, and engineering innovation. With strong financial support and access to cutting-edge research facilities, it offers a valuable opportunity to contribute to the future of sustainable energy systems.
Eindhoven University of Technology PhD 2026 in Statistical Bioinformatics
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If you are planning to pursue a PhD in Europe with strong financial support, the opportunity at Eindhoven University of Technology is one of the best options available. This fully funded PhD position in Statistical Bioinformatics offers competitive salary, advanced research training, and access to a world-class innovation ecosystem in the Netherlands.
Overview of the PhD Position
Host Institution: Eindhoven University of Technology
Location: Eindhoven
Department: Mathematics and Computer Science
Supervisor: Jeanine Duistermaat
Degree Level: PhD
Deadline: May 16, 2026
Duration: 4 Years
Employment Type: Full-time
Research Focus
This PhD project focuses on statistical data integration in biomedical research, particularly using advanced models for complex biological datasets.
Key research areas include:
Development of latent variable models for multi-omics data
Statistical modeling of longitudinal biological datasets
Integration of datasets such as:
Proteomics
Metabolomics
Transcriptomics
Assessing model performance and goodness-of-fit
Creating R packages for practical implementation
The research contributes directly to improving understanding of disease mechanisms, diagnosis, and treatment strategies.
Scholarship Benefits
The PhD position offers a strong financial and professional package:
Monthly salary between €3,059 – €3,881
Annual bonuses:
8.3% year-end bonus
8% holiday allowance
Pension scheme and paid leave benefits
Travel, remote work, and internet allowances
Access to:
High-quality research infrastructure
Training and career development programs
Sports and campus facilities
Support for international candidates, including relocation assistance
Eligibility Criteria
To qualify for this PhD position, applicants must meet the following requirements:
Master’s degree in:
Mathematics
Statistics
Or a closely related field
Strong background in:
Statistical modeling
Data analysis
Interest in biomedical applications and interdisciplinary research
Good communication and academic writing skills
English proficiency (minimum C1 level)
Additional advantages:
Experience with biological datasets
Programming skills (especially in R or similar tools)
Responsibilities
Selected candidates will:
Develop new statistical methods for multi-omics data
Apply models to real-world biomedical datasets
Build and maintain software tools (R packages)
Collaborate with interdisciplinary research teams
Present research at conferences and publish findings
Contribute to teaching (10–15% workload)
Application Process
To apply, candidates must submit:
Motivation letter
Updated CV (including publications and references)
Academic transcripts
Contact details of referees
Applications must be submitted through the official online portal. Incomplete or email submissions are not accepted.
Why Choose TU Eindhoven?
Eindhoven University of Technology is located in the Brainport Eindhoven region, one of Europe’s leading technology hubs. The university is known for:
Strong collaboration with high-tech industries
Cutting-edge research in AI, data science, and engineering
A highly international academic environment
Practical, impact-driven research approach
Final Thoughts
This PhD in Statistical Bioinformatics is ideal for candidates who want to combine advanced mathematics, data science, and biomedical research in a fully funded European program. With strong academic support and industry connections, it offers an excellent pathway for a research career in data-driven healthcare.
University of Luxembourg PhD in Civil Engineering 2026
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The University of Luxembourg is offering a fully funded PhD position in Civil Engineering with a focus on hybrid composite structures. This doctoral opportunity is part of the European HySCom project, aimed at developing next-generation structural systems using advanced materials such as UHPC and steel-concrete composites.
The position is hosted by the Faculty of Science, Technology and Medicine (FSTM) and provides a strong combination of experimental research, numerical modelling, and industry collaboration.
PhD Position Overview
Level of Study: PhD (Doctoral Researcher)
Institution: University of Luxembourg
Faculty: Faculty of Science, Technology and Medicine (FSTM)
Department: Engineering (DoE)
Supervisor: Markus Schäfer
Location: Luxembourg City (Kirchberg Campus)
Duration: 36 months
Start Date: June 15, 2026
Salary: €41,976 per year (gross, full-time)
Language Requirement: English (minimum B2 level)
Project Overview – HySCom
This PhD position is part of the Eurostars HySCom project, focusing on the development of innovative hybrid composite columns combining:
Reinforced concrete
Structural steel
Steel Fibre Reinforced Ultra-High Performance Concrete (SFRUHPC)
The project is conducted in collaboration with a leading German industrial partner, providing real-world engineering applications alongside academic research.
Research Areas
The doctoral research will include:
Material characterization of concrete and UHPC
Development and optimization of UHPC mixtures
Experimental testing (small-scale and large-scale structural tests)
Push tests and column tests
Advanced nonlinear finite element modelling (Abaqus)
Fire and ambient condition simulations
Structural design model development
Parametric studies and model validation
Key Responsibilities
The selected candidate will:
Conduct laboratory-based experimental research
Develop and validate computational models
Perform 3D nonlinear FEM simulations
Publish results in international journals
Present findings at global conferences
Support teaching and academic activities
Eligibility Criteria
Applicants must meet the following requirements:
Education
Master’s degree in:
Civil Engineering
Structural Engineering
Related engineering discipline
Technical Skills
Strong knowledge of:
Structural engineering
Steel–concrete composite systems
Construction materials (concrete, UHPC)
Familiarity with:
Eurocodes (EN 1990, EN 1992, EN 1993, EN 1994)
Experience with:
Nonlinear FEM (preferably Abaqus, GMNIA)
Additional Requirements
Interest in experimental and numerical research
Strong analytical and problem-solving skills
English proficiency (minimum B2 level)
Salary and Benefits
This is a fully funded doctoral position offering:
€41,976 annual gross salary
Full-time employment (40 hours/week)
Access to advanced laboratory and simulation facilities
Collaboration with industry partners
Opportunities to attend international conferences
Multicultural research environment
Required Application Documents
Applicants must submit:
Curriculum Vitae (CV)
Motivation letter
Academic transcripts
Contact details of 1–2 referees
Applications must be submitted through the official online system. Email applications are not accepted.
How to Apply
To apply for this PhD position:
Prepare all required documents
Submit your application through the official University of Luxembourg HR portal
Apply as early as possible (rolling selection process)
Contract Details
Position Title: Doctoral Researcher
Contract Type: Fixed-term (36 months)
Working Hours: Full-time (40 hours/week)
Campus: Kirchberg, Luxembourg
About the Faculty (FSTM)
The Faculty of Science, Technology and Medicine at the University of Luxembourg is a multidisciplinary hub covering:
Engineering
Computer Science
Physics and Mathematics
Life Sciences and Medicine
The Department of Engineering focuses on innovative and sustainable solutions for modern infrastructure and industry challenges.
Why Apply for This PhD?
This opportunity is ideal for candidates who want to:
Work on cutting-edge composite materials and structures
Gain hands-on laboratory and simulation experience
Collaborate with industry partners
Build an international research career in Europe
Contribute to sustainable infrastructure development