Research Fellow in Integrative Omics Data Analytics - Institute of Cancer and Genomic Sciences - 103702 - Grade 7

Position Details

Institute of Cancer and Genomic Sciences

Location: University of Birmingham, Edgbaston, Birmingham UK

Full time starting salary is normally in the range £34,980 to £44,263 with potential progression once in post to £46,974

Grade: 7 

Full Time, Fixed Term contract up to September 2026 

Closing date: 19th May 2024 

This role is also open as an internal secondment opportunity which would need to be agreed by your current line manager.

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 and implementation of multi-omics frameworks and the ambition to identify potential translational opportunities.

We are integrative analytics and AI lab lead by Dr. Animesh Acharjee working on state-of-the-art methods leveraging AI methods. The post holder will have a strong background in -omics data derived from metabolomics, transcriptomics, microbiomics etc. together with data science. 

The successful candidate will have an extensive experience with big data analysis, statistical methodologies and machine learning for investigating complex diseases and should be driven by the translation of these data to addressing current biomedical challenges. 

Role Summary

Fixed term for 2 years from early September 2024 offering a considerable scope for innovation in the interdisciplinary research. 

The post holder will be part of the Centre for Health Data Science, a hub of collaborative expertise made up of academics and clinicians, focussed on digital epidemiology, clinical bioinformatics, learning health systems, and artificial intelligence for health. Strong links also exist with the Birmingham University Hospitals NHS Trust via the Institute of Translational Medicine.

This post will be funded by the $6.4M Wellcome Leap programme awarded to the University of Birmingham to study Dynamic Resilience. Our project, entitled Towards the trialling of geroprotective agents at scale in clinical populations: closing fundamental knowledge gaps.

The purpose of the new role is to lead Wellcome Leap WP 1c and interact with other stakeholders across multiple departments. We require applicants with a strong background working with multiple omics data types, applying statistical and machine learning techniques to identify important associations and interactions between different factors. A history of developing models using large data sources and methods (for example: Deep learning , GAN etc) , such as UK biobank or other cohorts is expected. The successful applicant will use their computational and statistical expertise to identify novel research opportunities to better understand complex diseases. 

Translational medicine is at the centre of our research, with a focus on providing insights for clinical decision making and developing tools to aid patient wellbeing. The applicant will be involved in the development of these tools, such as prioritizing variants to identify drivers in the multiple diseases using the statistical methods to predict therapeutic responses. This will involve preparation of data through rigorous quality control and gold standard bioinformatics pipelines.

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, Biomedical Engineering, Bioinformatics or computational Biology, including a firm grounding in analysis and integration of big data. Candidates with excellent computational and quantitative skills are encouraged to apply. 

Main Duties

• Develop integrative strategies for a diverse set of omics data (metabolomics, transcriptomics, microbiomics etc.), integrating the outcomes to investigate complex disease in a multi-omics framework
• Apply statistical and machine learning and deep learning algorithms to diverse data of different multi omics data sets and quality to identifying associations and causal relationships driving diseases. 
• Manage and analyse large datasets for analysis using efficient data structures and providing infrastructure for sharing resources.
• 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.
• Apply knowledge in a way which develops new intellectual understanding. For example Deep learning based methods, GAN, generative AI etc. 
• 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.
• 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.
• Promotes equality and values diversity acting as a role model and fostering an inclusive working culture.

Person Specification

• PhD (or one near to completion) in health data science, computer science, artificial intelligence, computational biology, bioinformatics, or similar, or PhD in a healthcare area with a substantial omics component in their work. Candidates with excellent ML/AI, computational and quantitative skills are encouraged to apply. 
• Ability to:
  • Demonstrate an understanding of both biomedicine and bioinformatics.
  • 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.
• Expertise Scripts in R/Python, especially working with libraries and packages useful for bioinformatics such as the Bioconductor package. 
• Extensive experience working with omics data and large datasets.
• Proven and extensive experience with pipelines across multiple data types, such as RNA sequencing or Single Cell RNA sequencing 
• 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 High Performance Computing facilities and linux systems.
• Knowledge of the protected characteristics of the Equality Act 2010, and how to actively ensure in day to day activity in own area that those with protected characteristics are treated equally and fairly.

Further particulars can be found here
Informal enquiries to Dr Animesh Acharjee, email: a.acharjee@bham.ac.uk

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