We are a world class research-intensive university. We deliver teaching and learning of the highest quality. We play a leading role in economic, social and cultural development of the North East of England. Attracting and retaining high-calibre people is fundamental to our continued success.
Research Assistant Salary: £28,331 – £29,176(with progressionto £30,046 per annum)
Research Associate Salary £30,942 – £32,817 (wirh progression to £40,322 per annum)
Closing Date:17 August 2021
This exciting inter-disciplinary position is a collaboration between the Medical School and the School of Computing at Newcastle University. You will develop and apply Data Science and Machine Learning / AI methods to support a precision and personalised medicine approach to the early diagnosis and accurate prognosis of advanced/end-stage of liver disease. The deployed solutions must also address explainability, reliability, and trustworthiness requirements in order for the outcomes to acceptable to clinicians as scientifically valid.
The post is funded by LITMUS (Liver Investigation: Testing Marker Utility in Steatohepatitis), which is a large, international, multi-disciplinary project, funded by the European Innovative Medicines Initiative 2 Joint Undertaking and aims to develop, validate and qualify better biomarkers for the testing of Non-Alcoholic Fatty Liver Disease (NAFLD).
NAFLD is a common condition, strongly associated with the Metabolic Syndrome. NAFLD prevalence has increased dramatically in concert with the rapidly progressing epidemics of both adult and childhood obesity and T2DM. This condition often progresses into liver inflammation states leading to fibrosis (NASH), with associated high mortality. Despite a substantial body of past research, NAFLD is characterised by substantial inter-patient variability in severity and rate of progression liver inflammation states with associated high mortality. The problem of predicting which patients will progress, and how quickly, is therefore both complex and relevant.
This position is full time and available on a fixed term basis until 31 October 2022.
For informal enquiries please contact Prof. Paolo Missier, Professor of Large Scale Info Management, via email: firstname.lastname@example.org
As part of our commitment to career development for research colleagues, the University has developed 3 levels of research role profiles. These profiles set out firstly the generic competences and responsibilities expected of role holders at each level and secondly the general qualifications and experiences needed for entry at a particular level.
• Develop and validate Data Science (Machine Learning, AI) methodologies for the integrated analysis of multi-faceted datasets, obtained primarily but not only from the LITMUS data registry aimed at understanding their role in predicting and explaining the early detection of liver inflammation states in a large cohort of NAFLD patients.
• Develop and validate elements of a metadata management infrastructure designed to support explanations and justifications for the insights provided by the Data Science methods (point 1)
• Contribute to high impact scientific publications, presenting at scientific meetings and disseminating scientific results to a variety of audiences including the general public.
• Contribute to grant applications submitted by others and in time develop own research objectives and proposals for own funding.
• Co-ordinate own work with that of others, deal with problems which may affect the achievement of research objectives and contribute to the planning of the project.
• Work to deadlines and manage, with support, competing priorities.
• Ensure that personal knowledge in relevant fields of study is kept up to date.
Knowledge, Skills and Experience
• Ability to rapidly learn and apply Data Science techniques
• Working familiarity with popular computing and data analysis environments, including R and/or Python and commonly used associated libraries (e.g. Pandas, Scikit)
• High level of analytical and problem solving capacity
• Ability to communicate complex information clearly, both orally and through the written word, including publications
• Experience in data analysis and statistical modelling or computational biology
Attributes and Behaviour
• A strong attitude to constant learning, especially new data analytics techniques that apply specifically to medical and healthcare datasets;
• A positive attitude to develop independent critical thinking and approaches to addressing research problems.
• A strong attitude to work as part of an inter-disciplinary team of Data Scientists, Medical Scientists at multiple levels of seniority.
Completed PhD, or be due to complete doctoral studies within 6 months of applying, in one of:
• Biomedical Science,
• Computer Science or Mathematics and Statistics, with specific qualifications in Big Data management and Data Science
Newcastle University is committed to being a fully inclusive Global University which actively recruits, supports and retains colleagues from all sectors of society. We value diversity as well as celebrate, support and thrive on the contributions of all our employees and the communities they represent.We are proud to be an equal opportunities employer and encourage applications from everybody, regardless of race, sex, ethnicity, religion, nationality, sexual orientation, age, disability, gender identity, marital status/civil partnership, pregnancy and maternity, as well as being open to flexible working practices.
The University holds a silver Athena SWAN award in recognition of our good employment practices for the advancement of gender equality. The University also holds the HR Excellence in Research award for our work to support the career development of our researchers, and is a member of the Euraxess initiative supporting researchers in Europe.
We understand how important the full employment package is to our colleagues at Newcastle University and we are committed to providing a great range of benefits and discounts for all. You can learn more about what is available here on ourBenefitsWebsite page.
Requisition ID: 9187