[Jobs] UK Fully funded PhD student position in causality and healthcare University of Edinburgh (Deadline Feb 16, 2022)

[Sotirios Tsaftaris]

As part of the Canon Medical and RAEng funded project on Healthcare AI [1], 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 but no later than September 2022.  (Application deadline Feb 16 2022) 

About the Project

We frequently hear that AI will aid the work of experts. To succeed in this an AI must make accurate and confident predictions, generalizing to new and unseen data. Yet we still train AI models via supervision (i.e. by providing several examples) and require diverse data to do so. There must be a better AI that can understand concepts in the data even without explicit supervision, and behave well even on unseen data. The limits of supervision are particularly profound when we consider a more multimodal view to sensory input using both visual and text input, or consider asking an AI to make predictions about the future. Ultimately our goal is to develop decision support systems that can predict and assess the influence of healthcare treatments and interventions. To achieve this, this AI must be able to distinguish correlation from causation and to jointly learn the concepts and any causal relationships between them and the desired output task or tasks.  

Thus, topics of interest for this PhD position include:

-representation learning (to learn concepts);

-causality (to learn relationships between concepts);

-generative models (to constrain the representations within a distribution space); and

-digital twinning of data generation and acquisition processes (to augment what we can describe physically and incorporate within the causal structure).

The candidate will:

- join VIOS [3] a dynamic, international team of several academics, postdocs and students working in the area of healthcare and deep learning at the University of Edinburgh –a powerhouse in AI, engineering and medicine;

- contribute to an exciting project where deep learning meets imaging and other healthcare data;

- collaborate with the Edinburgh-based R&D centre [4] of Canon Medical –a conglomerate in healthcare;

- interact with several clinical experts within the UK, Europe, the USA and Japan.  

Funding Notes

Tuition fees + stipend are available for Home/EU and International students

This position is fully funded for 42 months (3.5 years) and is open to all students with a preference for UK/EU nationals. International tuition fees can be covered for exceptional candidates. Funding source: Canon Medical and RAENG.

To apply 

Candidates must apply via the UoE system (select PhD engineering 3 years ensure that you provide the title of this PhD and the name of the supervisor in the statement, cover letter etc). The research proposal of 2 pages is required. We do not look for the novelty of your ideas and in that sense it is not a research proposal per se but a reflection of your thoughts on the topic. The system will require you to include reference letter providers and their recommendations.

https://www.ed.ac.uk/studying/postgraduate/degrees/index.php?r=site/view&id=947 

The candidate can email Prof. Tsaftaris for inquiries. In the latter include a CV, mention this position in the subject, but note that this does not constitute a formal application.

Eligibility: 

A first class (or strong 2:1) honours degree or Distinction Masters level degree in Engineering, Computing, Mathematics, Physics, or relevant discipline is required. Candidates with an MSc equivalent training will be preferred. Demonstratable evidence of knowledge of machine learning (e.g. via coursework, projects, publications, work experience), and computational frameworks such as PyTorch, TensorFlow (e.g. via coursework or public repositories) are required. Evidence of prior publications of high caliber (e.g. in computer vision, image analysis or processing or machine learning) are desired but not essential criteria. The candidate should have a high level of analytical and investigative skills and a strong mathematical background. Ability to work within a team, collaborate and inspire others are essential criteria; thus, good communication and desire to own the project are sought-after abilities. 

Closing Date: 

Wed, Feb 16, 2022

Further information 

https://www.eng.ed.ac.uk/studying/postgraduate/research/phd/causal-representation-learning-robust-healthcare-predictions 

References

[1] Project page https://vios.science/projects/raeng

[2] Tutorial on disentangled representations, https://arxiv.org/abs/2108.12043 and https://vios.science/tutorials/dream2021

[3] VIOS website https://vios.science

[4] Canon Medical Research Europe website https://research.eu.medical.canon

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Professor Sotirios A Tsaftaris
Canon Medical/Royal Academy of Engineering Research Chair in Healthcare AI
Chair in Machine Learning and Computer Vision
Turing Fellow
School of Engineering, University of Edinburgh, 
Rm 2.06, Alexander Graham Bell, King’s Buildings, 
EH9 3FG, Edinburgh, UK
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