Join us

Team

Currently we have open positions, see below.

Why Join VIOS

We are an elite team of investigators at the University of Edinburgh, the University of Nottingham and Canon Medical—powerhouses in AI, healthcare, natural sciences and industry. There are several reasons to join our team:

  1. Full funding to do world-leading research We typically offer full funding (home and international fees and living costs/stipend) for several positions thanks to several sponsors.
  2. World-leading research and team We are a great team of investigators with years of experience in AI at The University of Edinburgh, a pioneer in AI for over 60 years. We aim high in terms of achievements but offer a stimulating and supportive environment.
  3. Unleash your creativity Unleash your creativity and explore uncharted territories in interdisciplinary AI, driven by our passion to address societal challenges and improve lives. We train the next generation of thought leaders to not only create ground breaking AI theory and methods but to be innovation ready individuals. This maximises career prospects.
  4. Future career prospects that match your aspirations Join our vibrant community of thought leaders and embark on a rewarding career path, following in the footsteps of our esteemed alumni who have excelled in industry and academia worldwide. Examples include: Google, Apple, FAIR, University of Nottingham, CMU, Ultromics, TU Darmstadt and many more.

If you wish to join the group as a PhD student or a postdoc, read below about open positions and funding opportunities. Please read well the instructions on how to contact us.

Current opportunities

We currently have two open positions.

  • CHAI PhD positions We are now recruiting for two PhD positions as part of the CHAI AI Hub on causal AI for medical imaging in partnership with Canon Medical. The positions are described here alongside information on how to apply. Please note that we will be reviewing applications as early as January 10, 2025. We have also collated questions on a FAQ document which we advise you look over.

Past opportunities

  • Four PostDoctoral Research Associate Positions in Causal AI: We are for four enthusiastic postdoctoral researchers to join our team led by Prof. Sotirios Tsaftaris in the prestigious high-profile CHAI AI Hub funded by EPSRC to help us develop new causal AI methods as applied to a variety of healthcare applications co-created within an ecosystem of partners and stakeholders. Our aspiration is to change the future of healthcare precisely because we devise better AI methods rooted in causal. Deadline 17 June 2024. To apply Review details and apply now here

  • PhD student in Causal Digital Twins: We have full funding for a position in causal AI to drive the simulation of digital twins. This is inspired by applications in healthcare and in particular Computer Assisted Surgery. Very interesting questions arise here: How do we learn to co-train a causal AI and a digital twin from scarce data in a compute efficient manner? What happens if the few real data we have are biased? We will be reviewing applications as they arrive on a rolling basis starting from December 15, 2023 (early application is encouraged). We would like to have someone start by September 2024 the latest, but earlier is also possible and welcome. To apply visit this page. Include the name of Prof. Tsaftaris in the statement, under funding add “Project funding by Prof. Tsaftaris”, and in the proposal page draft two pages with the title “Proposal for Causal Digital Twin PhD topic of Tsaftaris” and include your understanding of causal AI and how it might help drive digital twin simulations. (Note that we are not looking for ideas here per se; we just want to see how you shape your thoughts.) Once you have applied please email your application number to Prof. Tsaftaris.

  • PhD student in Foundation Models in CV: We have full funding for a position in leveraging foundation generative models for applications where training data are scarce. Our goal is to create ready-to-use computer vision bespoke models inspired by applications in health and agriculture. Very interesting questions arise here: e.g. Do synthetic data always help? Can we prompt the generation of data that correct for (real) data biases? Can we prompt with examples to train generic solvers based on primitives? We will be reviewing applications as they arrive on a rolling basis starting from December 15, 2023 (early application is encouraged). We would like to have someone start by September 2024 the latest, but earlier is also possible and welcome. To apply visit this page. Include the name of Prof. Tsaftaris in the statement, under funding add “Project funding by Prof. Tsaftaris”, and in the proposal page draft two pages with the title “Foundation Models in CV PhD topic of Tsaftaris” and include your understanding of foundation models and how currently foundation models are adapted to work in small data settings. (Note that we are not looking for ideas here per se, but we just want to see how you shape your thoughts.) Once you have applied please email your application number to Prof. Tsaftaris.

  • PhD student in Vision-Language models: We seek applications for a position to investigate multi-modal models, with respect to the underlying data representations, in relation to their respective modalities. Self-supervision from image–text pairs has enabled the development of flexible general-purpose vision–language models, recently in specialised domains such as biomedicine and radiology. Questions that arise include: are specialized encoder and decoder architectures for different data modalities optimal?, can modality agnostic representations, e.g. implicit neural representations bring advantages to multi-modal models?. We will be reviewing applications as they arrive on a rolling basis starting from December 15, 2023 (early application is encouraged). We aim for someone to start by September 2024 latest, but earlier is also possible and welcome. To apply visit this page. Include the name of Dr. McDonagh in the statement, and in the proposal page draft two pages with the title “Vision-Language models PhD topic of McDonagh” and include your understanding of Vision-Language models and implicit neural representations (e.g. functa). (Note that we are not looking for ideas here per se, but we just want to see how you shape your thoughts.) Once you have applied please email your application number to Dr. McDonagh.

  • PhD student in Automatic behaviour monitoring through privacy-preserving multimodal data analysis in health and care applications: As part of the ACRC, we are looking for a PhD student (international students eligible) to work on privacy-preserving mechanisms for affective beahaviour monitoring. Deadline Jan 30, 2024. Primary Supervisor: Luz (Medical School and Usher Institute); Other supervisors: Haider (VIOS), De La Fuente Garcia (Medical School), Tsaftaris (VIOS). Apply directly via this FindAPhD link. Pay attention to the application instructions for this particular position.

  • PhD student in Causal data-driven insight and prediction in care : As part of the ACRC, we are looking for a PhD student (international students eligible) to work on causality and care decision making. Deadline Feb 3, 2023. Supervisors: Tsaftaris and Harrison (Medical School and Usher Institute). Apply directly via this FindAPhD link. Pay attention to the application instructions for this particular position.

  • PhD students for the CDT in Biomedical AI: Deadline January 13, 2023. Prof. Tsaftaris is listed as a supervisor for the CDT in biomedical informatics so interested students that are interested in the intersection of healthcare and AI are more than welcome to contact Prof. Tsaftaris with an expression of interest before application. State clearly the purpose of contacting us and for which opportunity. Information to apply is here.

  • Causal representation learning for robust healthcare predictions : As part of the Canon Medical/RAEng Grant, we are looking to expand the team with a highly motivated PhD student working on disentangled representations, computer vision, and medical image analysis to start as soon as possible. Full funding and tuition fees for exceptional international candidates available too. Apply now for quicker consideration (deadline Nov 30, 2022). Check the details at the school of engineering or FindAPhD pages.

  • PostDoc on Causal Representation Learning from Rare Data (CLOSING SOON, 21 October 2022): We are looking for an enthusiastic postdoctoral researcher to join our team led by Prof. Sotirios Tsaftaris in a prestigious high-profile project (funded by EPSRC New Horizons). Prior work in our group (Hartley & Tsaftaris, arXiv 2022 and Jegorova et al, arXiv, 2021) has shown that supervised AI models are very susceptible to spurious correlation even when it is extremely rare. We don’t know how the representations are affected, or how shortcut learning contributes, or whether this is a pure artifact of stochastic training. You will interact with Amazon Web Services, Canon Medical and visit ELLIS Units in Europe. Deadline 21 October 2022. Apply now here

  • PhD student in Explainable machine learning for risk prediction in later life care : The project aims to develop explainable machine learning algorithms to predict the risk of harms from common healthcare interventions in older people approaching the end of life. Project with Advanced Care Research Centre. Check here for details.

  • PhD students for ELLIS: Prof. Tsaftaris as a Fellow for ELLIS welcomes applications from interested candidates as part of this unique in the world PhD program. You are more than welcome to contact Sotos with an expression of interest but first review carefully the application page here. Note the deadline is Nov 15 2022.

Important information for PhD students applying

  • We welcome applications from outstanding and ambitious students, with the potential of becoming extraordinary scholars. We select unfortunately few of the applications that we receive, and the only selection criterion is excellence.
  • Successful applicants have a very diverse background, including engineering, computer science, mathematics, physics, etc. Our research group is very diverse for gender, race, nationality, career ambition, etc. We strongly value the diversity in our group, and thus applicants from groups typically under-represented in academia are strongly encouraged to apply.
  • Being fluent in both spoken and written English is essential. We accept the following English language qualifications at the minimum grades specified:
    • IELTS Academic: total 6.5 with at least 6.0 in each component
    • TOEFL-iBT: total 92 with at least 20 in each section
    • PTE Academic: total 61 with at least 56 in each of the Communicative Skills scores
    • CAE and CPE: total 176 with at least 169 in each paper
    • Trinity ISE: ISE II with distinctions in all four components Your English language qualification must be no more than three and a half years old from the start date of the programme you are applying to study, unless you are using IELTS, TOEFL, PTE Academic or Trinity ISE, in which case it must be no more than two years old.
  • Making Informal Enquiries Informative: Applications [for open positions] must be submitted through the online University system. Informal enquiries about open positions (excluding questions on the application process and scholarships) can be sent by email to Prof. Tsaftaris or any of the other supervisors). Please clearly state which position you are applying for in the subject line and your questions in the email and confirm that you have read this webpage. (Emails that do not clearly mention PhD topics from the ones listed above will not receive a timely response.) Questions on the application process and scholarships should be directed to the Postgraduate Office of the School of Engineering: EngGradOffice@ed.ac.uk. Within your enquiry, it is strongly recommended that you attach a detailed CV and the following: Details of every qualification; Academic career history; Highlight any academic success; Ranking within your cohort (including its size); If you have published any conference or journal papers, provide links to the publication(s) and state your contribution.
  • Self-funded students: We occasionally accept strong students that are self-funded preferrably via scholarship and extremely rarely on own funds. Please do state this clearly upon any informal inquiry made on the subject line.

Visiting students

  • We welcome visitors from all over the world and we have had succesful and rewarding experience from all our visitors. Such visits must go through approval by the University and there are considerations w.r.t. visas, available visitor slots, etc. Hence we select unfortunately few of the applications that we receive. If you want to potential visit us do state this clearly in the subject line, attach a CV, mention a potential duration, potential start etc and of course a research direction that you are interested to pursue.

Interns students

  • At the moment we do not accept applications for paid internships externally from the UK (but we can host paid interns within the University and potentially the UK).

Email

Sotos

E-Mail: S.Tsaftaris (at) ed.ac.uk

Steven

E-Mail: s.mcdonagh (at) ed.ac.uk