Research Fellow

Location
Edinburgh, UK
Salary
Competitive
Posted
Jun 30, 2020
Closes
Jul 30, 2020
Ref
052465
Contract Type
Full Time
The Centre for Medical Informatics at the Usher Institute within The University of Edinburgh seeks an experienced data scientist to conduct original research as a key member of the British Heart Foundation (BHF) and Alan Turing Institute funded project "Uncovering retinal microvascular predictors of compromised brain haemodynamics in small vessel disease" aimed at discovering associations between the compromised brain haemodynamics observed in small vessel disease (SVD) and retinal vascular phenotypes derived from optical coherence tomography angiography (OCTA) images.

The successful candidate will be able to capitalise on data already acquired in two ongoing longitudinal studies on cerebral SVD and over a decade of experience in retinal image processing in Edinburgh. Co-PIs Wardlaw and Bernabeu are internationally recognised experts in SVD and cardiovascular mathematical modelling, respectively.

The successful candidate will conduct original research, centred around a) establishing a standard for OCTA image segmentation with particular emphasis on its robustness and applicability to routinely acquired data, b) developing novel metrics to characterise the structure and temporal evolution of microvascular networks based on the principles of Network Science and Machine Learning, c) investigating associations between OCTA-derived retinal microvascular phenotypes and compromised brain haemodynamics (cerebrovascular reactivity, cerebral blood flow, and blood brain barrier leak as well as cross-sectional and longitudinal lesion and diffusion tensor imaging changes).

Successful candidates will be in possession of a PhD degree in a relevant discipline, demonstrable experience in computer programming, image processing, and machine learning; and a track record of published work. Previous experience in biomedical image processing and/or experience in clinical studies is desirable. Due to funding, salary will be in the range £33,797-£35,845 initially.

The post is available from 1 September 2020, full-time (35 hours per week) for 24 months.

Please include your CV and a supporting statement with details of how you meet the knowledge, skills and experience required for this post.

Informal enquiries may be directed to Dr Miguel O. Bernabeu, Senior Lecturer (miguel.bernabeu@ed.ac.uk)

Further Particulars

1. Job Details

Job title: Research Fellow

Deanery/Support Department: MGPHS / Usher Institute

Unit (if applicable): Centre for Medical Informatics

Line manager: Dr Miguel O. Bernabeu

2. Job Purpose

To conduct original research, centred around a) quantification of retinal vascular structure based on image processing of existing OCTA retinal datasets (inc. machine learning approaches), and b) discovery of associations between compromised brain haemodynamics observed in small vessel disease (SVD) of the brain and vascular phenotypes measured in OCTA retinal images. To prepare papers for publication of the results and to engage with the rest of the study investigators and ensure delivery of a cutting-edge multidisciplinary programme of research.

3. Main Responsibilities
  • To conduct original research as a key member of the British Heart Foundation and Alan Turing Institute funded project "Uncovering retinal microvascular predictors of compromised brain haemodynamics in small vessel disease" aimed at discovering associations between the compromised brain haemodynamics observed in small vessel disease (SVD) and retinal vascular phenotypes derived from optical coherence tomography angiography (OCTA) images. This includes responsibility for conducting research on a collective basis with responsibility for delivering results within the project timelines. More specifically: a) to establish a standard for OCTA image segmentation with particular emphasis on its robustness and applicability to routinely acquired data, b) to develop novel metrics to characterise the structure and temporal evolution of microvascular networks based on the principles of Network Science and Machine Learning, c) to investigate associations between OCTA-derived retinal microvascular phenotypes and compromised brain haemodynamics (cerebrovascular reactivity, cerebral blood flow, and blood brain barrier leak as well as cross-sectional and longitudinal lesion and diffusion tensor imaging changes.) 70 %
  • Maintain accurate and up-to-date records to document the research progress. Take a lead role in preparing papers for publication of the results. Present data at group meetings, section meetings, and conferences to make data available for other workers. Regular reporting of progress to the PI/other members of the research team is expected. Presentation of research findings at national and international level (if appropriate). 5%
  • Contribute to the dissemination and publication of own/research team's research findings (as appropriate). 5 %
  • To prepare research proposals and applications to external funding bodies based on a line of future research. 5 %
  • To continually update knowledge and understanding in the field or specialism, and update skill base within the defined research area. 10 %
  • To provide guidance and supervision for student projects and/or instruction of students in the use of equipment/demonstration of techniques. 5 %

  • 4. Planning and Organising

    The post-holder will plan and manage own programme of research activity on an ongoing basis, to ensure that the research is conducted in accordance with the research timetable. Assist more junior members of the research team in planning and scheduling of their workload, in accordance with the demands of the overall project.

    5. Problem Solving

    The post holder is expected to resolve most problems using accumulated experience, with only the most serious non-standard issues reported to the line manager for assistance. To use creativity and initiative to identify areas for research, develop new research methods, diversify the research parameters. Use initiative to analyse and interpret research data, and draw conclusions from it. Use initiative to help other researchers in the team to resolve project problems and develop new techniques and methods, as appropriate.

    6. Decision Making

    Taken independently: Organise own workload according to priority and adapt as necessary, setting of short-term time-lines, design experimental set-up to address specific research aims
    In collaboration with others: Problem solving and data interpretation, experimental design and discussion of short-term research aims and potential new research strategies
    Referred to manager: Overall timelines, changes of direction, response to serious and unexpected events, identification of the best way forward and interpretation of complex data (although input to these areas is expected).
    Level of Direction Given: Line manager will offer general orientation and advice, in addition to support in developing and implementation of research strategy, there will be an appropriate degree of independence

    7. Key Contacts/Relationships
    Internal: PIs (Dr Miguel O. Bernabeu and Prof. Joanna Wardlaw) and members of the immediate research team (other researchers, technical support), build internal contacts and links to share information, students
    External: Collaborating researchers worldwide, external networks to share information and develop links as appropriate

    8. Required Knowledge, Skills and Experience

    Essential

    • PhD (or near completion) with relevant post-graduate research experience
    or equivalent professional qualification and/or experience.
    • Ability to communicate complex information clearly, orally and in writing
    • Expertise in relevant approaches and models, analytical techniques and methods
    • Excellent written, verbal and interpersonal communication skills
    • Ability to work independently, and as part of a team

    Desirable

    • Proven track record of publishing research outputs.

    9. Job Context and any other relevant information

    This post is part of the British Heart Foundation and Alan Turing Institute funded project "Uncovering retinal microvascular predictors of compromised brain haemodynamics in small vessel disease" aimed at discovering associations between the compromised brain haemodynamics observed in small vessel disease and retinal vascular phenotypes derived from optical coherence tomography angiography images.

    Cerebral small vessel disease (SVD) is a common neurological disease which causes up to 45% of dementias and about 20% of all strokes worldwide. The cause of the underlying pathology is poorly understood and there is no proven treatment. A limitation in human SVD research is that current magnetic resonance brain imaging technology has millimetre resolution while the vessels where SVD start are microscopic. However, retinal and cerebral microvasculature are developmentally related, and the former can be fully resolved in routinely acquired optical coherence tomography angiography (OCTA) retinal imaging.

    In this project, we will use Data Science to deeply phenotype retinal images in two ongoing clinical SVD studies. First, we will develop machine learning approaches for OCTA image segmentation and Graph Theory approaches for structural phenotyping. Second, we will uncover associations between structural and functional retinal phenotypes and SVD-related compromised brain haemodynamics. We expect this work to be an important step towards delivering Precision Medicine for SVD.

    Salary
    The role is grade UE07 and attracts an annual salary of £33,797 to £40,322 (pro rata) for 35 hours each week. Salary is paid monthly by direct transfer to your Bank or Building Society account, normally on the 28th of the month. Salaries for part-time staff are calculated on the full-time scales, pro-rata to the Standard Working Week.

    This post is available on a fixed term basis, with a working pattern of 35 hours per week for 24 months.

    Pension Scheme
    This role is grade UE07 and therefore the post holder is automatically included in membership of the Universities Superannuation Scheme (USS), subject to the USS membership criteria, unless they indicate that they choose not to join the Scheme.

    For further information please visit our pension's website: http://www.ed.ac.uk/schools-departments/finance/pensions/scheme-details/uss

    Right to Work

    In accordance with the Immigration, Asylum and Nationality Act 2006 and Immigration Act 2016 the University of Edinburgh, as an employer, has a legal responsibility to prevent illegal working and therefore must check that all employees are entitled to work in the United Kingdom (UK).
    To do so, the University requires to see original documents evidencing right to work in the UK before commencement of employment and this is normally carried out at interview. Details will be provided in any letter of invitation to interview.

    For further information on right to work please visit our right to work webpage

    If you are from outside the EEA and not currently eligible to work in the UK, there are visa routes that may be available to you, for example:
  • Tier 1 (Exceptional Talent): If you are an academic in the field of sciences; humanities; engineering; medicine; digital technology; or the arts, it may be possible for you to apply for a Tier 1 (Exceptional Talent) visa. This route requires you to apply to be endorsed as an internationally recognised leader or emerging leader in your particular field by a designated competent body (Arts Council England, British Academy, Royal Academy of Engineering, Royal Society, Tech City UK). However, if you are applying for a senior academic role, e.g. Professor/Reader there is an accelerated route to endorsement. Further information can be found on the UKVI website
  • Tier 2: The University is a UKVI licensed sponsor and is able to issue a Certificate of Sponsorship (CoS) to successful candidates who are offered highly skilled roles and meet the eligibility criteria. The CoS enables candidates to apply for a Tier 2 (general visa).

  • Please note if you were last granted leave to stay in the UK in any Tier 2 category in the 12 months immediately preceding an application and the leave has
    • ended or expired.
    • the CoS which led to that grant of leave was issued for more than 3 months, and
    • you are either:
    o applying for entry clearance from outside the UK, or
    o you are in the UK and had a previous period of Tier 2 leave, but then changed ('switched') into a different immigration category and now wishes to apply again under Tier 2.
    You must wait 12 months before applying again.

    Further information about whether you require a visa and other visa routes can be found at: www.gov.uk/check-uk-visa

    Application Procedure
    All applicants should apply online by clicking the "apply" button at the foot of this page. The application process is quick and easy to follow, and you will receive email confirmation of safe receipt of your application. The online system allows you to submit a CV and other attachments.

    Closing date: 31 July 2020 at 5pm.

    Interview date
    You will be notified by email whether you have been shortlisted for interview or not.

    The University reserves the right to vary the candidate information or make no appointment at all. Neither in part, nor in whole does this information form part of any contract between the University and any individual.
    var links = document.querySelectorAll(".targetLink"), i, j, aTags, string; for(i=0; i Deanery of Molecular, Genetic and Population Health Sciences Molecular, Genetic and Population Health Sciences is one of three Deaneries in Edinburgh Medical School which, together with the Royal (Dick) School of Veterinary Studies, makes up the College of Medicine and Veterinary Medicine. The Deanery is headed by Professor Sarah Cunningham-Burley and comprises the Institute of Genetics and Molecular Medicine (IGMM), the Usher Institute of Population Health Sciences and Informatics, the Division of Pathology and the Edinburgh Clinical Trials Unit. The Deanery currently attracts annual research grants of around £40M, including a number of full programme grants, and has around 630 employees including 39 Professors, over 260 other academic members of staff and 330 members of support staff. The Deanery operates across three University of Edinburgh sites; the Western General Hospital campus, the Central Area, and Little France. Staff contribute undergraduate and postgraduate teaching and offer on-campus and on-line programmes. There is a vibrant PhD community in both IGMM and the Usher Institute.
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