Reference Quantity: ST0649

Particulars of normal

Bioinformaticians are scientists – specialists who use computational, knowledge analytical and knowledge mining methods that are utilized to a spread of issues within the life sciences, for instance, in pharmaceutical corporations within the technique of drug discovery and improvement. Roles require scientists who perceive life sciences, and who can work computationally with various and huge volumes of information derived from completely different life science actions – and function names and descriptions typically mirror this by utilizing barely completely different names for what’s broadly the identical computational skill-set. For instance, bioinformatics, computational biology, computational toxicology, Well being informatics, Medical informatics, Agri-informatics. This vary of titles mirror the significance of life-science-specific information coupled with the underlying (and generally specifically-adapted) knowledge science, statistics and computational expertise.

Broadly, bioinformatics is: Analysis, improvement, or software of computational instruments and approaches for increasing using life science, (inc. organic, chemical or well being) knowledge, together with these to accumulate, retailer, organise, archive, analyse, or visualise such knowledge; in such a means that aids improvement and software of data-analytical and theoretical strategies, mathematical modelling and computational simulation methods to the examine of such organic techniques.

A bioinformatician is commonly a part of a collaborative group or workforce of scientists, drawing collectively life scientists, statisticians and computational infrastructure specialists. Consequently, the bioinformatician should be capable of work throughout these disciplinary boundaries. The primary duties of such a job would come with the power to: 

  • Work as a part of an interdisciplinary workforce to assist life science experiments from the design stage by means of to knowledge evaluation and organic interpretation.
  • Develop appropriate plans for the storage and administration of organic knowledge, together with annotation and metadata, and implement these by means of add to public repositories and/or implementation of native databases.
  • Work with personal and/or public bioinformatics assets, taking into account the authorized, moral or confidentiality points of their use.
  • Critically consider uncooked organic knowledge and put together it for appropriate evaluation.
  • Decide essentially the most appropriate methodology for computational evaluation, contemplating organic and experimental relevance, and the place crucial construct and check analytical pipelines or write and check new algorithms.
  • Analyse organic knowledge and to interpret the consequence within the context of the experimental design and, the place crucial, in a broader organic context by means of integration with complimentary (typically public) knowledge.
  • Perform all knowledge dealing with, processing and evaluation with consideration of economic practices and steering together with documentation, reproducibility regulated processes and mental property (IP).
  • Talk the outcomes and their context to interdisciplinary scientific friends and take part in dissemination by means of writing papers and giving talks. Additional assist the understanding of others by means of supervision and coaching.

Necessities: Data, Abilities and Behaviours

The Bioinformatics Scientist may have information and understanding of:

  1. A subject aligned with the life science area, and the core experimental platform/knowledge producing applied sciences within the chosen area.
  2. How analysis is carried out in bioinformatics and throughout the broader context of interdisciplinary life sciences.
  3. The technical limitations and the underlying organic and experimental assumptions that impression on knowledge high quality.
  4. Particulars of omic-scale/big-data-driven life science making use of core platform applied sciences.
  5. The duties of working in manufacturing/business environments managing scientific knowledge – together with regulated environments (good observe, and IP/confidentiality necessities).
  6. Present approaches for modelling and warehousing of life science knowledge.
  7. Necessities for accountable, authorized or moral entry and use of organic knowledge, together with normal knowledge safety (GDPR) issues, identifiable private genomic & healthcare knowledge, and geographic biodiversity-related knowledge considerations.
  8. Ontologies and their use.
  9. Retrieval and manipulation of organic knowledge, together with knowledge mining, from public repositories.
  10. Strategies to combine, interpret, analyse and visualise organic knowledge units.
  11. Bioinformatics evaluation methodologies and experience in frequent bioinformatics software program packages, instruments and algorithms – together with workflow administration instruments.
  12. Frequent bioinformatics programming languages; algorithm design, evaluation and testing.
  13. The usage of appropriate model management instruments, software program sustainability practices and open supply software program repositories.
  14. Licensing limitations on using bioinformatics software program and knowledge reminiscent of open supply, industrial and tutorial utilization restrictions.
  15. Database design and administration, together with data safety issues and big-data applied sciences.
  16. Related big-data and excessive efficiency computing platforms together with Linux/Unix, native and distant Excessive Efficiency Computing (HPC), and cloud computing.
  17. Software of statistics within the contexts of bioinformatics and life science knowledge evaluation.
  18. Statistical and mathematical modelling strategies, and key scientific and statistical evaluation software program packages.
  19. Normal knowledge science approaches to life science issues, reminiscent of machine studying and synthetic intelligence (AI).
  20. The significance of information governance, curation, data structure and guaranteeing interoperability.
  21. Variations within the knowledge-base of various audiences, and essentially the most applicable technique of successfully speaking scientific and technical data.
  22. Communication fashions and methods which might be employed in a collaborative analysis atmosphere to impact change at particular person, workforce and organisational stage eg.  energetic listening expertise, teamworking, influencing and negotiation expertise.


A Bioinformatics Scientist can:

  1. Work with multi-disciplinary colleagues to design life-science experiments that can generate knowledge appropriate for subsequent bioinformatics evaluation.
  2. Present steering to experimental scientists on knowledge era methodology and dealing with to make sure the standard of information produced.
  3. Recognise and critically evaluate the format, scope and limitations of various organic knowledge.
  4. Outline the required metadata to be collected for particular datatypes and analytical approaches.
  5. Design and implement applicable knowledge storage codecs and related database construction.
  6. Select applicable computational infrastructure and database options – together with inside or exterior/cloud assets.
  7. Retailer and analyse knowledge in accordance with moral, authorized and industrial requirements, together with checking who has entry.
  8. Curate organic knowledge utilizing appropriate metadata, ontologies and/or managed vocabularies.
  9. Make use of appropriate programming languages and/or workflow instruments to automate knowledge dealing with and curation duties.
  10. Keep a working information of a spread of public knowledge repositories for organic knowledge.
  11. Put together knowledge for submission to applicable public bioinformatics knowledge repositories as required, being conscious of IP and/or moral and authorized points.
  12. Perform knowledge pre-processing and high quality management (QC) to organize datasets for bioinformatics evaluation.
  13. Decide the most effective methodology for bioinformatics evaluation, together with the number of statistical exams, contemplating the analysis query and limitations of the experimental design.
  14. Determine and outline applicable computing infrastructure necessities for the evaluation of such organic knowledge.
  15. Apply a spread of present methods, expertise and instruments (together with programming languages) crucial for computational biology observe – and;
  16. Contribute to (the place applicable, lead) analysis to develop novel methodology.
  17. Construct and check analytical pipelines, or write and check new algorithms as crucial for the evaluation of organic knowledge.
  18. Doc all knowledge processing, evaluation and implementation of recent strategies in accordance with good scientific practices and business necessities for regulatory course of and IP.
  19. Interpret the outcomes of bioinformatics evaluation within the context of the experimental design and, the place crucial, in a broader organic context by means of integration with complementary (typically public) knowledge.
  20. Receive knowledge units from personal and/or public assets – contemplating any authorized, privateness or moral points of information use.
  21. Perform the evaluation of organic knowledge utilizing applicable programmatic strategies, statistical and different quantitative and knowledge integration approaches – and visualise outcomes.
  22. Talk and disseminate bioinformatics evaluation and outcomes to a spread of audiences, together with multi-disciplinary scientific colleagues, non-scientific members of administration, exterior collaborators and stakeholders, grant/funding our bodies and the general public as required.
  23. Supervise and mentor colleagues and friends to develop bioinformatics information related to their particular life science topic expertise.
  24. Talk orally and in writing, and collaborate successfully with interdisciplinary scientific colleagues, and administration features to watch and handle folks, processes or groups.
  25. Handle their very own time by means of preparation and prioritisation, time administration and responsiveness to alter.


A Bioinformatics Scientist shall be aware of:

  1. Skilled requirements within the office in relation to: ethics and scientific integrity, authorized compliance and mental property, respect and confidentiality, and well being and security.
  2. The necessity to repeatedly develop their information and expertise in relation to scientific developments that affect their work, guaranteeing they proceed to offer related analyses, together with rising methods the place applicable.
  3. The continued want for consciousness of technical advances within the broader scientific area which will current alternatives for private and / or organisational improvement.
  4. The broader context (coverage, financial, societal, technological, authorized, cultural and environmental) wherein scientific analysis operates, recognising the implications for skilled observe.
  5. The should be enthusiastic, self-confident, self-aware, empathic, dependable and constant to function successfully within the function.
  6. The requirement to persevere, have integrity, be ready to take accountability, to problem areas of concern, to steer, mentor and supervise.



It’s anticipated that the length of the apprenticeship shall be usually 30 months.

Entry Necessities

Particular person employers will set the choice standards, nevertheless generally candidates may have a background in a life sciences topic or informatics/pc science. Apprentices with out Stage 2 English and Maths might want to obtain this stage previous to taking the endpoint evaluation. For these with an training, well being and care plan or a legacy assertion, the apprenticeship English and Maths minimal requirement is entry Stage 3 and British Signal Language {qualifications} are an alternative choice to an English qualification for whom that is their main language.


On completion, apprentices will maintain a Stage 7 Grasp’s Diploma qualification (a MSc., MSt., MRes., or a MSc by Res. relying on the supplier establishment) in Bioinformatics aligned to a science or expertise self-discipline related to their job function.


It is a Stage 7 diploma apprenticeship

Overview Date

Three years after approval of the usual.


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