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Apprenticeship training course

Bioinformatics scientist (degree) (level 7)

Specialists who use computational, data analytical and data mining techniques which are applied to a range of problems in the life sciences.

Qualification level
7
Equivalent to master’s degree.
Typical duration
30 months
Apprenticeship category
Health and science
Maximum funding
£18,000
Maximum amount government will fund
for apprenticeship training.
Skills
Skills an apprentice will learn
  • Work with multi-disciplinary colleagues to design life-science experiments that will generate data suitable for subsequent bioinformatics analysis.
  • Provide guidance to experimental scientists on data generation methodology and handling to ensure the quality of data produced.
  • Recognise and critically review the format, scope and limitations of different biological data.
  • Define the required metadata to be collected for specific datatypes and analytical approaches.
  • Design and implement appropriate data storage formats and associated database structure.
  • Choose appropriate computational infrastructure and database solutions - including internal or external/cloud resources.
  • Store and analyse data in accordance with ethical, legal and commercial standards, including checking who has access.
  • Curate biological data using suitable metadata, ontologies and/or controlled vocabularies.
  • Make use of suitable programming languages and/or workflow tools to automate data handling and curation tasks.
  • Maintain a working knowledge of a range of public data repositories for biological data.
  • Prepare data for submission to appropriate public bioinformatics data repositories as required, being aware of IP and/or ethical and legal issues.
  • Carry out data pre-processing and quality control (QC) to prepare datasets for bioinformatics analysis.
  • Determine the best method for bioinformatics analysis, including the selection of statistical tests, considering the research question and limitations of the experimental design.
  • Identify and define appropriate computing infrastructure requirements for the analysis of such biological data.
  • Apply a range of current techniques, skills and tools (including programming languages) necessary for computational biology practice – and;
  • Contribute to (where appropriate, lead) research to develop novel methodology.
  • Build and test analytical pipelines, or write and test new algorithms as necessary for the analysis of biological data.
  • Document all data processing, analysis and implementation of new methods in accordance with good scientific practices and industry requirements for regulatory process and IP.
  • Interpret the results of bioinformatics analysis in the context of the experimental design and, where necessary, in a broader biological context through integration with complementary (often public) data.
  • Obtain data sets from private and/or public resources – considering any legal, privacy or ethical aspects of data use.
  • Carry out the analysis of biological data using appropriate programmatic methods, statistical and other quantitative and data integration approaches – and visualise results.
  • Communicate and disseminate bioinformatics analysis and results to a range of audiences, including multi-disciplinary scientific colleagues, non-scientific members of management, external collaborators and stakeholders, grant/funding bodies and the public as required.
  • Supervise and mentor colleagues and peers to develop bioinformatics knowledge relevant to their specific life science subject experience.
  • Communicate orally and in writing, and collaborate effectively with interdisciplinary scientific colleagues, and management functions to monitor and manage people, processes or teams.
  • Manage their own time through preparation and prioritisation, time management and responsiveness to change.

Full information on Bioinformatics scientist (degree) (level 7) is available from the Institute for Apprenticeships and Technical Education.

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