Research Associate in Machine Learning for Genomics

at  Kings College London

Job id: 094245. Salary: £43,205 - £50,585 per annum, including London Weighting Allowance.
Posted: 14 August 2024. Closing date: 28 August 2024.
Business unit: IoPPN. Department: Biostatistics & Health Informatics.
Contact details: Alfredo Iacoangeli. Alfredo.iacoangeli@kcl.ac.uk
Location: Denmark Hill Campus. Category: Research.
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About us
This post will be based at the Department of Biostatistics & Health Informatics at King’s College London within the Bioinformatics team led by Dr Alfredo Iacoangeli. Our team currently include several staff and students and we have extensive experience in the development of Genomics, bioinformatics and machine learning tools and methods (https://github.com/KHP-Informatics/).
We are part of the Institute of Psychiatry, Psychology & Neuroscience (IoPPN). The IoPPN is a leading centre for mental health and neuroscience research in Europe. It produces more highly cited outputs (top 1% citations) on psychiatry and mental health than any other centre (SciVal 2023), and on this metric has risen from 16th (2014) to 4th (2023) in the world for highly cited neuroscience outputs. In the 2021 Research Excellence Framework (REF), 90% of research at the IoPPN was deemed ‘world leading’ or ‘internationally excellent’ (3* and 4*). More info about the IoPPN are available here www.kcl.ac.uk/ioppn/about
About the role
We are recruiting one highly motivated Postdoctoral Bioinformatician to join King’s College London in a new collaborative research programme. Through comprehensive genomic research that utilises large-scale multi-omics and clinical datasets (including WGS, SNP arrays, Methylation, RNAseq for tens of thousands of individuals), this programme aims to develop and validate machine learning solutions for precision medicine approaches and the early diagnosis of Motor Neurone Disease (MND).
The successful candidate will join a team of neuroscientists and computational experts at the King’s MND Care and Research Centre, where they will have a leading role in developing computational analysis methods and analysing large-scale multi-omics datasets comprising thousands of samples. These posts will be based in Dr Iacoangeli’s bioinformatics team at the Department of Biostatistics and Health Informatics but given the collaborative and multi-disciplinary nature of the programme, the expectation is that they will work closely with other members of the King’s MND Care and Research Centre (Professor Al-Chalabi lead) and Health Informatics unit (Professor Richard Dobson lead).
The postholder will also be expected to build upon current collaborations with the other members of the King’s MND centre based at the Department of Basic and Clinical Neuroscience, in addition to collaborating with the members of large international consortia such as the EU JPND funded STRENGTH, Brain-MEND and Project MinE consortia.
This is a full time, and you will be offered an a fixed term contract until 17/03/2026.
About you
To be successful in this role, we are looking for candidates to have the following skills and experience:

Essential criteria

• PhD qualified in relevant subject area (or pending results), e.g. bioinformatics, life sciences, biotechnology, biophysics, Data science, Artificial Intelligence, etc.
• UpToDate knowledge of omics technologies
• UpToDate knowledge artificial intelligence and machine learning methods applied to genomics
• Programming in at least one language (Python, Java, Bash, Perl, R)
• Proficient in Unix based systems and high-performance computing
• Publication records commensurate with grade
• Ability to work independently without direct supervision
• Excellent communication (written & verbal) skills
• Biomedical research experience

Desirable criteria

• UpToDate knowledge of machine learning methods applied to clinical data
• Research experience in Neuroscience
• Experience in grant writing
• Experience in supervising staff and PhD students

Downloading a copy of our Job Description
Full details of the role and the skills, knowledge and experience required can be found in the Job Description document, provided at the bottom of the next page after you click “

Please refer the Job description for details