View Vacancy -- MRC Postdoctoral Research Scientist in Machine Learning LMS - 2722

Overall purpose:

We are seeking a talented scientist to develop innovative machine leaning approaches for understanding human health using cardiovascular imaging. These approaches integrate large datasets including health care records, genomics and imaging to prioritize novel therapeutic targets and identify mechanisms that modify risk of disease.  

Applicants should have a track record of experience in machine learning, statistics and data science and will lead on developing models for precision medicine, genotype-phenotype association, and advanced prediction tasks. Knowledge of a wide range of statistical tools and clustering / prediction algorithms is required. Experience of using foundation models and generative AI would be an advantage.  Specific experience of using UK biobank data and human imaging would be desirable. The applicant should have proven programming experience including Python and R as well as using HPC and GPU environments.  

The Computational Cardiac Imaging Group works at the intersection of clinical imaging, bioinformatics, computer vision and molecular cardiology to explore the mechanisms underlying heart function. The group uses machine learning to analyse cardiac motion for predicting patient outcomes, discovering potential therapeutic targets and identifying genetic risk factors. We use a flexible and inter-disciplinary approach to research that moves between individuals, populations and model organisms.  

The post offers an exciting opportunity to work at the cutting-edge of translational medicine research in a vibrant and supportive multi-disciplinary team that crosses traditional scientific domains. The role involves performing semi-independent research as well as supporting other members of the group. The post holder will have the opportunity to attend scientific conference, and publish the results of their work in leading journals. There will also be an opportunity to contribute to external grant applications.  There is a vibrant and supportive scientific community at the LMS with outstanding opportunities for career development and training.

Key skills:

• Background in AI/ML and data science
• Experience of using large databases and data wrangling
• Excellent programming skills in R and Python – including use of Jupyter Notebooks and cloud computing resources
• Advanced knowledge in a range of predictive tasks, clustering techniques and inference modelling
• Knowledge of HPC environments, Git and Docker an advantage

Main responsibilities:

• To develop models for high dimensional clustering and prediction tasks using biomedical imaging
• Perform analyses both on premises and cloud compute
• To manage the work in collaboration with other members of the team and external partners
• To write and publish the work, as well as prepare grant submissions
• To take an active role in the academic work of the group and support the organisation as a whole
• To present at seminars and conferences as necessary
• To co-supervise MSc students
• Willingness to work out of normal working hours (including weekends) if the requirements of the project demand
• To contribute to the smooth running of the Group’s/Unit’s laboratories and, facilities with other scientists, clinicians, technicians and students within the laboratories
• To comply with the Institute, College, Division, and Unit safety practices and to attend courses on safety when appropriate
• Any other duties as may be deemed reasonable by Head of group as well as Head of Division

Education / Qualifications / Training required (will be assessed from application form):

Essential:

• PhD (or equivalent experience) in Data Science / Computational Science or a closely related discipline

Knowledge and experience (will be assessed from application form and at interview):

Essential:

• Excellent skills in R and Python with proven ability in programming and handling large datasets
• Proven ability to independently develop advanced AI architectures for medical research
• Experience of working in a multidisciplinary research group
• Excellent written communication skills in English

Desirable:

• Previous experience of DNAnexus or UKB Research Analysis Platform
• Experience in writing Bash scripts and using Linux environments
• Familiar with HPC scheduling and using Docker
• Good knowledge of Git for version control
• Experience of managing large databases and data wrangling
• Track record of software development and package creation

Personal skills / Behaviours / Qualities (will be assessed at the interview):

Essential:

• Ability to conduct reproducible research
• Ability to conduct a detailed review of recent literature
• Ability to develop and apply new concepts
• Creative approach to problem-solving
• Excellent verbal communication skills in English and the ability to deal with a wide range of people
• Ability to direct the work of a small research team and motivate others to produce a high standard of work
• Ability to organise own work with minimal supervision
• Ability to prioritise own work in response to deadlines
• Advanced computer skills, including word-processing, spreadsheets and the Internet
• Willingness to work as part of a team and to be open-minded and cooperative
• Flexible attitude towards work
• Discipline and regard for confidentiality and security at all times
• Willingness to work out of normal working hours (including weekends) if the requirements of the project demand
• Willingness to undertake any necessary training for the role
• Willingness to work predominantly on site

Additional information:

Applicants should submit a CV, names and contacts of two scientific references along with a cover letter stating why you are applying for this role (providing evidence against the requirements of the job as per the job description and person specification).

Please note that applications may be reviewed by both LMS and Imperial staff