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Research Fellow (Artificial Intelligence/Machine Learning) - Institute of Cancer and Genomic Science

Employer
University of Birmingham
Location
United Kingdom
Salary
£32,348 - £42,155,
Closing date
Dec 6, 2022
Position Details

Institute of Cancer and Genomic Sciences, College of Medical and Dental Sciences

Location: University of Birmingham, Edgbaston, Birmingham UK

Full time starting salary is normally in the range £32,348 to £42,155, with potential progression once in post to £44,737

Grade 7

Full Time, Fixed Term contract up to 30th April 2025

Closing date: 6th December 2022

Background

This is an exciting and unique opportunity for an ambitious PhD graduate or post-doctoral data scientist with the ability and confidence to lead the development of AI-based frameworks that cater for the integration and analysis of multimodal primary care, secondary care, qualitative, and prescribing data to optimise clinical decision making in patients with complex multimorbidities and polypharmacy, by using a patient similarity approach. The post holder will have a strong background in health data science, computer science, engineering with modern machine learning and artificial intelligence approaches, with experience of applying modern learning frameworks to health data, medical images and longitudinal data.The successful candidate will have a sound background in algorithm development, health data science and data manipulation and should be interested in the translation of this experience to address current biomedical challenges.

Role Summary

We are looking to recruit an enthusiastic research health data scientist, computer, scientist/clinical bioinformatician who will lead the development of AI-based approaches that cater for the integration and analysis of multimodal primary care, secondary care, qualitative, and prescribing data to optimise clinical decision making in patients with complex multimorbidities and polypharmacy, by using a patient similarity approach in close collaboration with domain experts.

The post holder will join a national consortium with expertise in multi-morbidity, ageing, artificial intelligence, health data science and qualitative methodologies. The team will work in partnership with the RSF to become a national exemplar of reproducible, secure and interoperable research in practice and demonstrating the utility of accessible research-ready data made available through rigorous engineering and technical standards. The post holder will be part of the Clinical Bioinformatics Group, led by Prof. Gkoutos, become a member of Health Data Research UK, and be based in the Institute of Translational Medicine where the post holder will reside as part of an interdisciplinary team.

The purpose of the new role is to lead the development and application of novel state-of-the-art machine learning within the area of health data science and bioinformatics. The post holder will have sound knowledge in computer science, data analysis and data integration. We anticipate the development and adaptation of novel machine learning algorithms to provide interpretable insights, with a focus on health data/bioinformatic approaches to unravel the mechanisms underlying human disease. Furthermore, the ideal candidate will have experience with modern interpretable AI approaches in several of the following areas: medical image processing and analysis using neural networks, attention-based learning, time-series, and the analysis of longitudinal data. Experience with sophisticated visualization approaches is a plus. We offer an excellent network of biomedical and technological collaborations, as well as opportunities for discovery validation and translation into clinic or pharma by domain experts.

The position requires the ability to independently take responsibility over scientific projects, strong teamwork and communication skills, reliability, attention to detail, and effective time management. Applicants should have a PhD or equivalent experience in Health Data Science, Computer Science, Artificial Intelligence, Biomedical Engineering, Bioinformatics, Statistics or Mathematics including a firm grounding in analysis and integration of big data. Candidates with excellent computational and quantitative skills matching the above AI approaches are also encouraged to apply.

Main Duties
  • Develop and apply cutting-edge AI & machine learning approaches within a real-world clinical setting in close cooperation with medical experts.
  • Manipulate, integrate, and analyse diverse data of different dimensions and quality, residing in distributed sources
  • Develop and apply cutting edge machine learning methods to integrate multimodal biological data with real-world clinical outcomes data in consultation with clinical experts
  • Drive novel applications and take responsibility over large and diverse projects
  • Develop research objectives and proposals for own or joint research, with assistance of a mentor if required
  • Contribute to writing bids for research funding
  • Apply knowledge in a way which develops new intellectual understanding
  • Disseminate research findings for publication, research seminars etc
  • Supervise students on research related work and provide guidance to PhD students where appropriate to the discipline
  • Contribute to developing new models, techniques and methods
  • Undertake management/administration arising from research
  • Contribute to Departmental/School research-related activities and research-related administration
  • Contribute to enterprise, business development and/or public engagement activities of manifest benefit to the College and the University, often under supervision of a project leader
  • Collect research data; this may be through a variety of research methods, such as scientific experimentation, literature reviews, and research interviews
  • Present research outputs, including drafting academic publications or parts thereof, for example at seminars and as posters
  • Provide guidance, as required, to support staff and any students who may be assisting with the research
  • Deal with problems that may affect the achievement of research objectives and deadlines

Person Specification
  • PhD (or near to completion) in Health Data Science, Computer Science, Artificial Intelligence, Biomedical Engineering, Bioinformatics, Statistics or Mathematics, or similar. Likewise, candidates with excellent ML/AI, computational and quantitative skills are encouraged to apply
  • Ability to:
    • Demonstrate an understanding of both biomedicine and informatics
    • Innovate and develop ideas into grant proposals
    • Learn and keep abreast of latest technological, methodological and software developments
    • Write concise and timely scientific papers and reports
    • Plan and prioritise work effectively to meet deadlines
  • Effectively communicate analysis results via presentations, visualizations or tools such as apps
  • Proven and extensive experience with machine learning methods for both model building and deployment
  • Experience working with medical images and/or time series and longitudinal data and large datasets
  • Ability to interact with academic and industry partners and explain complex ideas to non-scientists in a comprehensible way
  • Ability to work in a heterogeneous environment of diversely skilled individuals
  • Experience in image analysis and machine learning libraries (Python or R), attention-based learning
  • Experience in High Performance Computing facilities and Linux systems
  • Teaching skills with demonstrated experience
  • Experience with health care datasets and semantic based data integration is highly desirable

Further particulars can be found here

Informal enquires to Martha Holmes, email: m.holmes@bham.ac.uk

Valuing excellence, sustaining investment

We value diversity and inclusion at the University of Birmingham and welcome applications from all sections of the community and are open to discussions around all forms of flexible working .

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