Overview
- Qualification type: PhD
- Subject area: Machine Learning, Bioinformatics, Medical Image Processing.
- Start date: 1 May 2023 or as soon as possible.
- Duration: three years, full time
Project outline
As a Ph.D. researcher specializing in Cancer Modelling using Machine Learning, you will play a pivotal role in advancing the state-of-the-art in bioinformatics and medical imaging. This position offers an exciting opportunity to engage in cutting-edge research and contribute to the development of innovative machine learning based methodologies for cancer modelling, data driven discovery of new biomarkers, recurrence prediction, immunotherapy treatment response prediction and other various applications.
In this research, you are expected to develop novel methods for cancer data modelling and analysis using cutting edge machine learning and deep learning algorithms for bioinformatics and medical imaging to advance cancer diagnostics through analysis of heterogeneous information extracted from genomic and imaging data.
This Ph.D. project is in collaboration with Curenetics Ltd (https://www.curenetics.io/ ).
Key Responsibilities
- Conduct in-depth literature reviews and market analysis to identify current trends and challenges in this area of research.
- Design, simulate, and optimize machine learning based methods for multimodal data analysis, including genomic and imaging data, considering factors such as missing data, heterogeneous and asynchronous information.
- Collaborate with interdisciplinary teams, including bioinformaticians, engineers, biologists, oncologists, researchers, and industry partners, to validate and prototype innovative methodologies.
- Publish research findings in reputable journals and present results at conferences, contributing in patents and to the academic and scientific community.
Supervisors
- Principal supervisor: Dr Iosif Mporas
- Second supervisor: Dr Maria Braoudaki
Entry requirements
Essential
- A first or upper second-class degree (or equivalent) in a relevant discipline such as, computer science, electronic engineering, maths, etc.
- Very good knowledge of machine learning and deep learning.
- Ability to work collaboratively and manage time independently to meet deadlines.
- Problem-solving skills and attention to detail.
- Excellent oral and written English communication skills, including the ability to communicate with clarity on complex information.
- excellent IT literacy.
- Applicants must be self-motivated.
Desirable
- A relevant master’s degree will be an advantage.
- Publications in high-impact international journals and conferences.
- Experience in bioinformatics and/or medical imaging.
- Good knowledge of programming language Python preferably in Linux environment.
- Previous experience with state-of-the-art AI/ML software libraries.
Eligibility
The studentship is open to UK/EU and international applicants.
How to Apply
Informal enquires can be made to Dr Iosif Mporas ([email protected] ), Director Research Centre Networks and Security.
Please download and complete an application form
In section 11 you must provide a comprehensive personal statement of up to 500 words describing your motivation to do research on this project at the University of Hertfordshire, and providing information on how you meet any of the essential or desirable requirements described above.
Please also send with your application form:
- A research proposal not exceeding 1 page.
- Two academic references.
- Copies of qualification certificates and transcripts.
- Certification of English language competence (minimum IELTS 6.5 or equivalent) for candidates for whom English is not their first language.
Your completed application should be emailed to the Doctoral College
Interview dates: beginning of April 2024.
Expected studentship start date: 1 May 2024 (or as soon as possible thereafter).
Funding information
The award includes cover for UK home or international tuition fees and a stipend at standard UKRI rates. For 2023-2024 this is set at £18,622. The stipends usually increase annually in line with inflation. Applicants from outside the UK or EU are eligible.
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