KINGS COLLEGE LONDON

Early Stage Researcher

Location
London (Central), London (Greater) (GB)
Salary
£38,039 per annum, including Mobility Allowance; family allowance available, if applicable
Posted
15 Oct 2020
End of advertisement period
15 Nov 2020
Academic Discipline
Life sciences, Biological Sciences
Contract Type
Fixed Term
Hours
Full Time

The Department of Twin Research and Genetic Epidemiology (DTR) at King’s College London is recruiting an Early Stage Researcher (ESR) to a Disc4All, EU-funded training project, commencing 1 November, 2020. The Disc4All project is a consortium of academics and industry partners offering 15 ESR positions throughout the EU and UK – with an ambition to establish a novel framework enabling translational medicine to deliver for highly multifactorial disorders. The project is focussed on lumbar disc degeneration (LDD) – a leading cause of disability world-wide; incorporating, analysing and modelling large and far-ranging data sets to deliver clinical solutions.   

We are looking for an enthusiastic team member to lead the data mining of viable LDD phenotypes from TwinsUK (globally the most extensively phenotyped Twin registry) and other large epidemiological datasets for inclusion in Disc4All analysis. The candidate will work in data curation and experimental computational modelling and the implementation of models and simulations (M&S) of multiscale and multidisciplinary data (e.g. imaging, physics and biology).   

This ESR position involves PhD registration and lasts for 36 months. The role offers high-level and pioneering training in data integration, M&S technologies and bioinformatics with an aim to create traceable pathways between microbiome influences, disc infection, physical loading, cell metabolism, genetic polymorphisms and LDD clinical outcomes.  Training focuses upon the molecular and epidemiological data and biomedical use of innovative statistical techniques. Candidates will gain experience conducting genome wide association (GWA) meta-analysis and Mendelian randomisation (MR). The student will also proactively develop and execute new microbiome and genetic statistical methods. Skills acquired during this degree will be extremely transferable; graduates will have a broad range of opportunities to contribute extensively to multifactorial disorders.   

A  minimum of seven additional training programs are offered over the course of the degree – annual  winter and summer schools with one  advanced training event where ESRs and other consortium collaborators come together to discuss and constructively challenge the progress of the project. ESRs will benefit from a unique inter-domain collaborative experience, developing expertise in scientific communication and connection to renowned international researchers.   

This is an exciting opportunity to join a successful collaborative aspiring research team, working on an EU-ITN project investigating the biological basis of LDD.   

Applicants will at the minimum have an upper-second class (2.1) honours life sciences degree (or overseas equivalent). Only candidates who demonstrate an exceptionally strong academic background in data analytics, computational science or statistics will be considered. A publication record is highly advantageous. Excellent written and oral communication skills are expected.   

Applicants must have received their first degree qualifying them for PhD training within four years of the start date. Candidates must also meet the residency and mobility requirements of the Disc4All programme: At the time of recruitment the researcher must not have resided or carried out his/her main activity (work, studies etc) in the country of the recruiting institution for more than 12 months in the preceding 3 years immediately prior to recruitment.  

Upon completion of this PhD the candidate will be ideally and uniquely placed to adopt a leading role in industry, academia or the public sector.

This is a full-time post, fixed-term contract for 3 years.

Key responsibilities

  • Undertake TUK data mining and Disc4All LDD phenotype analysis and establish superior phenotype resolution

  • Establish gut microbiome and LDD associated markers – using GWAS and MR

  • Plan and manage own project work

  • Learn and apply current computational epigenetics technologies

  • Assist with the design and application of novel computational epigenetics technologies

  • Present findings and progress at DTR seminars

  • Liaise with and foster close working relationship with the other 14 Disc4All ESRs

  • Present to and constructively interact with ESRs at training events

  • Regularly report on research project progress to PhD supervisor

  • Liaise with all DTR members including research nurses, other statisticians, administrative and laboratory staff and as well as external collaborators and their teams

  • To plan daily workload to complete tasks assigned

  • Write up and disseminate your own research

  • To attend multi-disciplinary and Unit meetings and other meetings as required

  • To conduct computational epigenetics

  • To keep abreast of relevant literature in the areas of computational biology, bioinformatics, LDD, epigenetics and genetic epidemiology

  • To convert results into scientific presentations and publications

  • All ESRs will have the opportunity to take roles of both trainer and trainee at the biannual consortium training events

  • DTR academics take part in regular meetings and present results and reports.

  • The post holder will be part of the DTR epigenetic project team and will be expected to interact with other members of the team and department

  • To plan and execute computational epigenetics, GWA, MR etc.

  • Any other duties appropriate to the studentship as directed by the Programme Director or Chief Investigator

  • Write up results in the form of scientific presentations and publications

  • The role is office-based, however opportunities to work from home are made available to KCL staff and students where feasible. This department currently has reduced office contact time and has introduced social distancing measures

  • The role holder should show good listening and accuracy skills which are important when dealing with students and members of academic staff

  • This role involves PC use for a substantial part of the job

The above list of responsibilities may not be exhaustive, and the post holder will be required to undertake such tasks and responsibilities as may reasonably be expected within the scope and grading of the post.

Skills, knowledge, and experience

Essential criteria

  • Grade 2.1 or above in a biological subject (or equivalent)

  • Demonstration of strong computational, bioinformatics analytical skills

  • Ability to communicate effectively at all levels in a complex multi-disciplinary environment with the ability to produce concise verbal and written reports

  • Ability to meet competing and demanding deadlines

  • Experience in epigenetics research, computational methods and statistical analysis

  • Experience of working with various word processing computer software or similar (e.g. MS Word, Excel, Access, Latex)

  • Ability to use statistical analysis packages to a high standard, such as PLINK or other UNIX-based systems, for computational genomics within a research environment

  • Excellent organisational skills

  • Experience with computationally intensive analyses in large-scale datasets

  • Proactive approach to work

Desirable criteria

  • Publication record in the field of epigenetics, computational biology, or statistics, or genetic epidemiology

  • Experience of writing scientific manuscripts and abstracts

  • Programming skills, to include C/C++, R, Fortran, Java, perl, python

Further Information

This post is subject to Disclosure and Barring Service clearance.

This advertisement does meet the requirements for a Certificate of Sponsorship under Home Office regulations and therefore the university will be able to offer sponsorship for this role. 

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