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
Equivalent to master’s degree.
- Typical duration
- 30 months
- Apprenticeship category
- Health and science
- Maximum funding
Maximum amount government will fund
for apprenticeship training.
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.
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