Level 7 Bioinformatics Scientist (MRes) Degree Apprenticeship
Gain the skills, knowledge and behaviours needed to process, analyse and interpret complex biological data
Bioinformatics Scientist (MRes)
At least a 2:2 in a biology-related degree. We will also consider graduates from a computational background on a case-by-case basis.
Apprentices will require access to a computer running a Linux based operating system, either single boot, dual boot or virtual machine.
Level 2 (equivalent to grades 4-9 (A*-C) at GCSE) or above in English and Maths. Apprentices who do not provide suitable Level 2 English certification and do not hold an appropriate English language equivalent qualification from this list, will also need to provide an International English Language Testing System (IELTS) result that is dated within the last two years. The minimum requirement for this programme is an overall score of 6.5, with no less than a 6.0 in each of the individual elements. The university’s policy around this can be found here.
Be working in a job role that provides opportunities to learn the skills, knowledge and behaviours outlined in the Bioinformatics Scientist standard (external link). Apprentices must work a minimum of 50% of their time in England.
The apprenticeship route is only available to UK/EU/EEA nationals or apprentices who have lived and have had a right to work in the UK for three years or more.
Cost to the employer for 2022/23 entry is £18,000. Please see the funding information below. There is no cost to the apprentice.
||School of Veterinary Medicine and Science, Sutton Bonington Campus
Gain the skills, knowledge and behaviours needed to process, analyse and interpret complex biological data
The Bioinformatics Scientist Degree Apprenticeship equips employees with the applied computational skills, knowledge and behaviours needed to process, analyse and interpret complex biological data in an effective and reproducible way.
Developed in consultation with industry partners, this programme demonstrates state-of-the-art best practices, enabling apprentices to determine the most applicable methods and develop reproducible pipelines that will maintain the integrity of their analysis when working with big data.
Apprentices will develop the fundamental knowledge of statistics and bioinformatics methods to confidently evaluate biological datasets from a range of life science activities and determine the most suitable method for analysis.
Apprentices will learn the practical application of modern, flexible programming languages Python and R. These languages are widely adopted in biosciences and will provide apprentices with transferable skills that can be applied when using other languages.
They will also gain the skills and knowledge to test the validity of their results, ensuring that analysis is robust and reproducible, and interpret the results in the context of their research.
The programme is predominantly delivered via distance learning, with a masterclass week at the beginning of years one and two to accommodate topics best taught in person. With an emphasis on practice, apprentices will be encouraged to apply taught knowledge on given data sets and real data from their workplace.
The apprenticeship features
Initial needs assessment
As part of the application and enrolment process, we will carry out an individual needs assessment. This will enable us to determine existing levels of skill and knowledge, and build a personal plan for each apprentice that will set out all the learning, tutorial support, and resources provided by the University.
As part of our continued support for each apprentice, we carry out a mixture of face-to-face and online termly tripartite reviews between the employer, apprentice and the University. The aim is to formally assess progress in the academic programme and work-based learning.
Apprentices are assessed on the taught components with reflective portfolios and practical data analysis tasks. They will then go on to complete their research project. The degree apprenticeship also includes an end point assessment, which comprises of a review of their final project and portfolio, followed by an interview with an independent assessor.
Each of our degree apprenticeship programmes are designed to include full support for the apprentice and their employer. We provide:
- an account manager to look after the employer relationship
- a degree apprenticeship officer to support each apprentice throughout the end-to-end programme
- an assigned academic work-based mentor for each apprentice
- workplace visits during the apprenticeship
- a dedicated academic management project supervisor
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Who is it for?
The programme is ideal for scientists working within life sciences who are required to analyse large biological data sets as part of their role. These may be employees who are already working in a bioinformatics role and would like to formalise their skills and knowledge, or life sciences graduates who are training in a bioinformatics role.
The programme is also suitable for academic researchers who would like to develop their computational biology skills to aid their research, allowing them to carry out analysis of large datasets in-house.
Please note, as the course is focused on computer programming within biology, it is mostly suitable for individuals with biology-related knowledge. However, we will also consider graduates from a computational background on a case-by-case basis.
Read Dr Sarah Storr's story
Course structure and modules
The degree apprenticeship is divided into three phases, with the majority of the content taught online via distance learning.
The taught modules develop the apprentices' understanding of the subject, and equip them with the skills needed to complete the research project dissertation that culminates in a masters degree. With a strong emphasis on practical learning, the aim is for apprentices to analyse data using a variety of methods, and write a Masters dissertation. Where appropriate, they will be encouraged to get their research published.
All online learning involves regular mandatory tutorials, with tutor support available throughout the course. Apprentices also have access to online forums where they can discuss work with their peers and specialists.
Masterclass weeks are held at the start of years one and two. They are designed to support and prepare apprentices for the online components of the programme.
In week one, the masterclass gives apprentices the opportunity to meet the teaching team – and each other. We encourage them to network, team build, create a cohort identity and develop a peer support group.
Apprentices can use the masterclasses to get to grips with the tools and terms used throughout the course, as well as discuss potential projects and formulate research questions.
In the second masterclass week, held at the start of year two, apprentices will begin to prepare for their research project. They will learn techniques for scientific writing, using referencing software, and how to critically evaluate scientific literature.
Phase one: taught content (months 1-12)
The first 12 months will focus on equipping the apprentices with the necessary skills to become an integral part of a multidisciplinary team carrying out life sciences research.
Continual formative feedback from the online modules will be provided alongside masterclass days, virtual tutoring and open forums. Together, these complement the taught content and weekly work activities from the team of experts and their on-the-job mentor. This level of support will help the apprentice tackle challenges and offer a way of thinking through problems.
This module is designed to build an understanding of commonly used bioinformatic techniques. It enables apprentices to begin to interrogate and interpret sequence data, and learn about the key limitations to certain methods. It also develops skills in how to test pipelines and compare advantages and limitations – working with the constraints of experimental design parameters.
The module will include:
- DNA sequencing and genomics
- genome variation
- database mining
- measuring gene expression
- data interpretation
- protein structure
Introduction to Statistics
This module will introduce statistics used in research, together with the accompanying principles of meta-analysis. It will cover methods of statistical test selection, and how to confidently test the results for validity and reproducibility.
One of the key learning outcomes is to give apprentices the techniques to integrate, interpret, analyse and visualise biological data sets – and apply statistics in the context of bioinformatics.
The teaching will cover:
- variables and distributions
- parametric and non-parametric tests
- systematic reviews and meta-analysis
Programming in Python
The Programming in Python module is designed to introduce Python as a programming language – including Python syntax, functions, lists and dictionaries. Apprentices will develop a practical understanding of programming concepts, with hands-on sessions exploring how they can be used to work with data, code in Python and analyse imagery.
Programming in R
R is a popular language and environment used for statistical computing and graphing in bioinformatics.
This module is designed to enable apprentices to understand the pivotal role R can play in data analysis, visualisation, interpretation and statistical tests. Over the duration of the module, they will learn important advanced data analysis techniques using machine learning, which can be applied on future projects.
Phase two (months 12-24)
MRes Research Project
With the topic agreed in advance by the University, apprentice and employer, this module will enable the apprentice to research, plan, design, gather data, analyse and document their findings of a novel study linked to computational biology.
This module will equip apprentices with the ability to communicate and disseminate bioinformatics analysis and results to a range of audiences from both the scientific and non-science community. It will also teach perseverance, integrity, responsibility and the confidence to challenge areas of concern – qualities found in the real world of work.
Phase three (months 24-30)
The third year gives the apprentice six months to complete their end-point assessment (EPA).
Apprentices will be eligible to progress on to the EPA once they have completed their MRes in bioinformatics, vocational competency log and all parties agree their readiness as set out in their individual learning plan.
An independent End-point Assessment Organisation will assess each apprentice against the Bioinformatics Scientist End-point Assessment Plan, which requires apprentice to:
- produce a synoptic report and presentation
- deliver a viva style presentation
- produce a Vocational Competency Evaluation log
Performance in the EPA will determine the apprenticeship grade of distinction, pass or fail. Successful apprentices will be awarded an apprenticeship certificate.
Why choose a degree apprenticeship?
As an employer, a degree apprenticeship is an excellent way to demonstrate a commitment to your new and existing employees’ learning and professional development. This route offers a strong recruitment and retention incentive by enhancing the skills of your workforce, boosting morale and nurturing talent, and improving the productivity and quality of your service.
The Level 7 Bioinformatics Scientist Degree Apprenticeship was created with industry to directly address the industry’s skills gaps. By investing in this training, you will enable your staff members to develop the skills to:
- perform comprehensive analysis of big data in house
- identify bottlenecks and potential short comings of certain analysis methods
- ensure the validity and reproducibility of analysis
- streamline analysis pipelines using modern programming languages
For the apprentice, the benefits of choosing this route are many. There are no tuition fees, they can earn while they learn, and they will gain practical knowledge, skills and accredited qualifications. The Bioinformatic Scientist Degree Apprenticeship allows employees to develop specialised bioinformatics skills in a formalised way, demonstrating their effectiveness and expertise in this field.
Why choose the University of Nottingham
The University of Nottingham is a pioneering university that provides an exceptional education and an outstanding student experience. We deliver world-leading research that transforms lives and societies.
For this programme, apprentices will have the opportunity to collaborate with and be supported by the University’s Digital Research Service and the Advanced Data Analysis Centre (ADAC), which provides data-driven research and innovation within academia and industry.
Formed and housed in the schools of Veterinary Medicine and Science and Computer Sciences, ADAC has a proven track record of carrying out research on a variety of projects, ranging from small proof-of-concept studies with a handful of data points to large national data infrastructure projects.
It is one of the largest collections of bioinformaticians, data scientists and research software engineers in UK universities and has contributed to securing more than £45 million of research funding since its creation in 2012.
About The School of Veterinary Science
Our School of Veterinary Medicine and Science has an excellent reputation for teaching, research and innovation, as well as dedicated facilities for apprentices to develop their theoretical and practical skills. The school houses academics from the Bioinformatic and Computational Biology research group, who will offer training and mentorship throughout the apprenticeship.
We are the only veterinary school to hold this award worldwide, recognising excellence in student engagement.
Careers and professional development
Apprentices will gain a recognised qualification that will help fill a skills and capability gap within the industry. This will offer significant opportunities to advance life sciences in the coming decades.
The skills, programming and statistics training will enable apprentices to be confident to design, conduct and critique research programmes. They will be able to use modern programming languages and work with multi-disciplinary colleagues to analyse the data of life science experiments and generate data suitable for subsequent bioinformatics analysis.
Information for employers
The cost for the Apprenticeship for 2021/22 entry is £18,000.
Apprentices do not pay programme fees. The programme fees are paid for by the employer and there are a number of funding options available.
Are you eligible for funding?
Funding eligibility depends on the number of people you employ, your company’s annual payroll and the age of the apprentice.
If you have a wage bill above £3 million, you can use your Apprenticeship Levy contributions to cover the programme fees. If you do not have sufficient levy payments to cover the full cost of the programme fees, you may be eligible for 95% government funding to cover the shortfall.
If you have a wage bill under £3 million, you can still access our programmes for your employees. You may be eligible for 95% government co-investment.
Incentive payment for hiring a new apprentice
As part of the government’s ‘Plan for Jobs’, to aid the UK’s economic recovery from COVID-19, there is a temporary incentive payment for those who hire a new apprentice between 1 April and 30 September 2021.
If apprentices meet the eligibility criteria you may be able to claim:
- £3,000 for apprentices regardless of age
To be eligible the apprentice must:
- be a new employee to the business
- have a contract of employment start date between 1 April and 30 September 2021 (inclusive)
- not have been employed by the employer within the six months prior to the contract start date. To find out more about the funding options available, and your eligibility, please get in touch with our degree apprenticeship team
As an employee, apprentices are entitled to a wage and paid time off to study. You will not have to pay Class 1 National Insurance for apprentices under the age of 25.
Contact the degree apprenticeship team