Opportunities and Vacancies

Vacancies

DevOps Engineer

DevOps Engineer

Institute: University of Manchester
Location: Oxford Road, Manchester
Hours: Full time. 1 January 2018 until 31 August 2018 in the first instance.
Salary: £31,604 to £38,833 per annum according to experience
Closing date: 11 Dec 2017

We have a vacancy for a DevOps engineer in the busy and exciting Centre for Health Informatics, with an initial focus on eLab projects.

Solving complex problems in health increasingly requires collaboration between different groups and data must be combined from different locations. The Centre for Health Informatics leads the development of the eLab Platform, a Virtual Research Environment for health. The eLab provides a single web-based interface for researchers to collaborate, manage data and run analysis programs, with the aim of furthering our understanding of disease.

In this post, you will have an opportunity to help to drive and support high-profile emerging technologies in areas including cloud computing, big data analytics and security. You will have the chance to apply your skills and knowledge to improve the University’s in house developed ‘eLab’ research infrastructure. You will support the automated deployment, configuration and testing of this key platform across multiple outward facing and international projects and programmes. You will have a passion for technology with a genuine enthusiasm to make a difference to the health and well-being of the population. You may have opportunities to travel internationally to study new technologies and to work alongside our stakeholders and partners.

As an equal opportunities employer we welcome applicants from all sections of the community regardless of gender, ethnicity, disability, sexual orientation and transgender status.  All appointments are made on merit.

More information on the university website

https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=14385
Principal Software Architect

Principal Software Architect

Institute: University of Manchester
Location: Oxford Road, Manchester
Hours: Full time. 1 January 2018 until 31 August 2018 in the first instance.
Salary: £39,992 to £49,149 per annum according to experience
Closing date: 11 Dec 2017

The Centre for Health Informatics is seeking a software architect.  We have a vacancy for a Principal Software Architect to provide key technical leadership and strategic direction in the busy and exciting Centre for Health Informatics, with an initial focus on eLab projects.

Solving complex problems in health increasingly requires collaboration between different groups and data must be combined from different locations. The Centre for Health Informatics leads the development of the eLab Platform, a Virtual Research Environment for health. The eLab provides a single web-based interface for researchers to collaborate, manage data and run analysis programs, with the aim of furthering our understanding of disease.

In this post, you will have an opportunity to gain experience with high-profile emerging technologies in areas including cloud computing, big data analytics and infrastructure security. You will have the chance to apply your skills and knowledge to develop the architecture of the eLab platform and inform the strategic direction of the team. You will have a passion for technology and developing software, combined with a genuine enthusiasm to make a difference to the health and well-being of the population. You may have opportunities to travel internationally to study new technologies and to work alongside our stakeholders.

As an equal opportunities employer we welcome applicants from all sections of the community regardless of gender, ethnicity, disability, sexual orientation and transgender status.  All appointments are made on merit.

More information on the university website.

https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=14386
Software Developer

Software Developer

Institute: University College London
Location: 222 Euston Road, London NW1 2DA
Hours: Full time. Available immediately until 30 September 2021
Salary: £43,023 – £50,753 per annum
Closing date: 10 Dec 2017

Duties and Responsibilities

Applications are invited for a Software Developer within a vibrant, multidisciplinary informatics team to play a leading role in the new, exciting and ground breaking IMI2 EU Bigdata@Heart project, a €20 million research programme using healthcare data to deliver better care for people with heart attacks, heart failure and the commonest heart rhythm disturbance, atrial fibrillation. In addition, the role will be expected to contribute to our Healthcare Informatics, Genomics/Omics, and Data Science (HIGODS) programme as part of the NIHR Biomedical Research Centre (BRC).

The position will be embedded within the Precision Health Informatics Data Lab (phidatalab.org), a pan-London informatics group that sits across the Farr Institute UCL, and King’s College London. The successful candidate will work on a number of smartphone- and wearables-based BigData@Heart mHealth studies, contributing code directly to the mHealth platform we are actively developing as part of the €25m IMI2 RADAR-CNS (RADAR-CNS.org, github.com/RADAR-CNS).

The candidate will have an interest in the integration of phone and wearable data with electronic health records and omics and will therefore link directly to other projects including our leading electronic health record (EHR) based clinical informatics platforms for real-time decision support, natural language processing, trial recruitment and research such as CogStack (@cogstack; github.com/CogStack and EU projects such as KConnect.eu).

This post is funded until 30 September 2021 in the first instance.

Key Requirements

The Appointee will have a strong background in one or more relevant disciplines including: software development, streaming analytics, bioinformatics, clinical, biomedical, health informatics, and natural language processing and computer science.

Relevant Master’s degree and.or PhD degree (biological science, statistics computer science, bioinformatics or equivalent) or demonstrable significant relevant experience is desirable. J2EE and extensive experience. Android App development; ability to write code that clearly expresses its purpose such that it can be maintained and extended; software maintenance, refactoring, and enhancement of existing applications; and significant Java experience are essential.

Interested candidates are welcome to contact Professor Richard Dobson (r.dobson@ucl.ac.uk  ) for an informal discussion.

You can find the job advert on the UCL website.

Other Opportunities

Fully funded PhD at the Department of Biostatistics, University of Liverpool

Fully funded PhD at the Department of Biostatistics, University of Liverpool

Web usage data in clinical trials – how can we determine dose?

The use of web based interventions in clinical trials is on the increase, as the internet provides an accessible mechanism for delivering intervention without the need for participants to travel to a clinic. However, it does not appear that the effectiveness of web interventions is being linked back to the actual usage of the intervention.

Collection of intervention use, or “dose”, data is important to inform causal analysis methods accounting for actual intervention use (rather than simply analysing according to randomisation, using “intention to treat”). In the context of an online intervention, however, it is not immediately obvious how best to define and measure “dose”.

Participants’ use of an online intervention can be recorded and monitored using various techniques, including Google Analytics (GA), server log data and customisable call backs to the projects servers; however, the reliability of these approaches is not guaranteed. In particular, it is likely that many users are unaware of the inaccuracies associated with GA data.

This project seeks to guide trialists on best practice of collection and use of online intervention usage data, to ensure consistent and reliable comparisons of web intervention “dose” to be evaluated across studies. In-house generated web usage data and trial data will be used to compare GA data with in-house server log and video data, to demonstrate the extent of GA inaccuracies and determine best practice for capturing accurate representation of web usage. The project will demonstrate how to use web usage data to inform causal analyses, to ascertain whether certain patterns of web use correspond to improved outcome, and will culminate in guidelines and toolkit for trialists on how best to collect, report and analyse web usage data as part of online intervention trials.

Person specification: The ideal candidate would demonstrate an interest in the use of web based interventions for clinical research, with a BSc/MSc in a relevant discipline demonstrating statistical/numerical skill.

Training and support: The student would be provided with all relevant IT and statistical training by supervisors in Liverpool and colleagues in Lancaster, Nottingham and UCL.

For further information contact Dr Susanna Dodd (s.r.dodd@liv.ac.uk) or visit www.findaPhD.com

PhD Studentship: Deep Learning Discovery & Visualization from Longitudinal Data

PhD Studentship: Deep Learning Discovery & Visualization from Longitudinal Data

This project aims to apply deep learning techniques on the large, rich bioresources available in Dundee (e.g. goDARTS) to discover novel biomarkers for high-prevalence conditions like diabetes and complications, CVD and dementia.

The focus is on deep learning, a class of machine learning algorithms which has pushed forward the field dramatically, and is increasingly being deployed in data mining/data analytics in genomics, healthcare and many other disciplines.

The student will learn about deep learning and deep network architectures as well as statistical packages (e.g. R) and “conventional” statistical methods.

The aim is to explore the potential of deep learning to discover biomarkers in image data (especially), and to visualize the relevant image features in a way suitable for human interpretation.

The project is a collaboration with the VAMPIRE/CVIP group in Computing (SSEN), which hosts state-of-the-art NVIDIA hardware to run specialised DL architectures.

(This PhD Studentship is funded by the MRC)

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PhD Studentship: Development of Innovative Methods for the Provision of Routinely Collected Medical Images Within Secure Safe-haven Environments

PhD Studentship: Development of Innovative Methods for the Provision of Routinely Collected Medical Images Within Secure Safe-haven Environments

Background

The medical digital images are routinely collected and archived by the NHS. Such images, especially when linked to other routinely collected health data, are extremely useful for research into areas including: early/preclinical diagnosis, disease progression, validation of treatment methods, development of novel computer vision methods for biomarker extraction, validation of novel algorithms and machine learning approaches and discovery and classification of disease types. Research using routinely collected imaging data for research has historically been under-utilised for many reasons including the impracticality of seeking consent of patients, challenges of de-identification of image data, absence of non-proprietary software for efficient handling this type of “big data” for research.

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PhD Studentship: Genomics & Retinal Biomarkers of Neurodegeneration

PhD Studentship: Genomics & Retinal Biomarkers of Neurodegeneration

This project is part of our investigation into novel biomarkers for risk assessment of neurodegenerative conditions, mainly dementia, from a rich set of patient data including full genetic profiles. The student will apply statistics and data analytics techniques (machine learning, deep learning), and learn to use state-of-the-art image measuring packages (e.g. VAMPIRE for retinal images) . It leverages large, cross-linked bioresources (eg goDARTS) which our team have accessed in previous projects. This project builds upon a 1.1M EPSRC grant (with Edinburgh) on multi-modal retinal biomarkers for vascular dementia (2015-8) and a Leverhulme project (2012-5) on retinal measurements and genetics, and complements starting projects like the 5M NIHR Global Health programme grant on diabetes-related data analytics. It is a strong strategic fit with our University strategy on health and biomedical informatics.

(This PhD Studentship is funded by the MRC)

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PhD Studentship: Personalising Primary Care Prescribing: Developing & Evaluating Integrated Informatics to Embed Pharmacogenomics Information into Clinical Decision-making in Real-time

PhD Studentship: Personalising Primary Care Prescribing: Developing & Evaluating Integrated Informatics to Embed Pharmacogenomics Information into Clinical Decision-making in Real-time

Background

There has been a revolution in our understanding of the genomics of drug metabolism, but apart from the treatment of cancer, this understanding has not much influenced clinical practice despite tens of thousands of Tayside residents having been genotyped and despite almost all primary care prescribing being done electronically. Key challenges include: (1) Prescribing decisions are made very quickly in a time-pressured environment and both under- and over-alerting are known to pose safety risks; (2) Linking clinical data in real-time poses information governance and security problems. The aim of this project is to develop and evaluate an informatics tool to make useful pharmacogenomics information available at the point of primary care prescribing.

(This PhD Studentship is funded by the MRC)

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Swansea University ESRC Wales Doctoral Training Partnership Studentships

Swansea University ESRC Wales Doctoral Training Partnership Studentships

Closing date: 1 February 2018
Location: Swansea University

Swansea University, supported by the ESRC Doctoral Training Partnership for Wales (Wales DTP), invites applications for PhD study, with the possibility of being awarded a fully-funded ESRC DTP studentship, available to start in October 2018. They expect to make doctoral studentship awards in Data Science, Health & Wellbeing, amongst many others.

walesdtp.ac.uk/studentships/
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