MSc Bioinformatics Scientist

Program Overview

This 30-month Bioinformatics Scientist Apprenticeship combines academic training with industrial experience. It provides the knowledge and skills necessary to become a competent bioinformatics scientist, culminating in an MSc degree and industry certification. The program emphasizes practical applications, with opportunities for hands-on work and real-world problem-solving, while promoting independent learning and lifelong skills development.

Program Outline

The first 24 months of this 30-month training programme are dedicated to providing you with both academic and industrial training opportunities and supporting you to achieve the MSc in Bioinformatics and the credits you require to undertake an endpoint assessment (EPA). After successful completion of the MSc component, you will have a further six months to undertake the EPA. This will certify you as a competent bioinformatics scientist.

Outline:

The Bioinformatics Scientist Apprenticeship (BSA) programme is 30 months long, involving a 24 months training period, during which you will spend at least 20% of your time in 'off the job' training to achieve 180 credits at Level 7. This is followed by a six months EPA period to achieve the MSc Bioinformatics degree and Bioinformatics Scientist Apprenticeship Certificate. The course is structured to progressively up-skill your knowledge, skills and behaviours to reach competence as a bioinformatics scientist.

Year 1 and 2

Compulsory Modules:

• Introduction to Genetics and Genomics: This module will develop your understanding of the key areas of genomics, human genetics and genetic variation.
You will also examine the genomics basis of diseases and how it can be used to improve health outcomes.
• Bioinformatics and Functional Genomics: This module will introduce you to basic practical sequence and structure analysis techniques, tools and resources.
You will also develop a strong foundation in 'omics and NGS analyses. There will be opportunities for you to apply bioinformatics and computational analysis to problem-solving in real healthcare or industry scenarios.
• Data Science for Bioinformatics: This module will introduce you to data science in bioinformatics.
• Advanced Bioinformatics and Genome Analysis: This module will help you to develop knowledge and skills that underpin the clinical application of bioinformatics.
The module will build on your genomics, bioinformatics and programming knowledge to develop an analysis strategy for a new service. There will also be opportunities for effective interdisciplinary team working.
• Machine Learning: Machine learning is an application of artificial intelligence that provides systems with the ability to automatically learn and improve from experience without being explicitly programmed.
This module familiarises you with some basic machine learning algorithms and techniques and their applications, as well as general questions related to analysing and handling large data sets. Several software libraries and data sets publicly available will be used to illustrate the application of these algorithms. The emphasis will be thus on machine learning algorithms and applications, with some broad explanation of the underlying principles.
• Bioinformatics Project: This module will give you the chance to demonstrate your ability to organise and carry out a major piece of work.
You will gather background information and research the literature and data. You will also design and execute a research plan to solve a bioinformatics problem, and discuss existing results and present your new findings through a series of written and oral presentations.

Optional Modules:

• Data Management in Healthcare (DSH): The aim of the module is to cover some of the developments in the broad range of data-driven healthcare.
The module also provides a good understanding of data structures, software development procedures and the range of analytical tools used to undertake a wide range of standard and custom analytical studies, providing data solutions to a range of healthcare issues.
• Big Data Analytics: In this module, learners will be provided with a balanced view of the theory and practice on big data analytics, allowing them to develop a variety of big data analytics knowledge and skills.
The module will also consider innovations and trends in technologies in conjunction with the requirements and implementation of health information systems.
• Policy Context of Improvement: The Policy Context of Improvement (Negotiated Work-based Learning) module provides you with theoretical and practical knowledge about the political context of improving healthcare services.

Assessment:

The course assessment strategy key principles are:

• a balance between the types of assessment and the overall workload of assessments
• the equitable nature of assessments across the course
• a balance between formative and summative work
• the integration of theory and practice
• the use of experience and reflection to develop critical awareness
• the relationship of the assessment to the leaning outcomes and the form of learning and teaching that takes place within the module
• the marking will tend to use predetermined grids and assessment forms to clearly identify the features that are assessed for all students in all assessments and to meet the level 7 Higher Education descriptors.
Assessment for the MSc course is designed, where possible, to simulate the variety of tasks that graduates from the course may encounter in relevant employment. Where necessary other academic assessment devices, such as a formal examination, defence of the proposal etc. are also used. Module tutors are the assessors in the majority of cases. However, we may also use peer and self-assessment where appropriate. Assessment types include:
• analysis and design and the production of appropriate artefacts
• portfolio of work
• workbooks
• oral presentations to tutors and peers
• viva voce
• case study reports
• synoptic reports
• technical reports
• development of design specifications
• research seminars
• critiques of own and peer work
• defence of a proposal
• written proposal
• major project
• examinations.

Teaching:

The range of teaching, learning and assessment strategies adopted on this course is intended to fulfil a number of principles, namely to:

• encourage you to develop as an independent learner
• promote an experiential approach to learning through volunteering, internship, networking and mentoring thereby providing links between learning and work
• accommodate and develop different preferred learning styles
• provide access to learning in different environments
• enable reflective practice through the use of learning logs, workbooks and learning agreements
• make our learning materials accessible to you through a variety of media
• use continuous formative assessment with a varied diet of summative assessments
• encourage you to engage in the pursuit of life-long learning
• develop higher level learning skills of analysis, synthesis and evaluation.
• lectures
• hands-on practical work
• whole group information-giving sessions
• workshops
• tutorials
• case studies
• blended e-learning
• group critiques.
As would be expected at masters’ level, there is an appropriate balance of theory and practice. In order to be successful you will need to demonstrate high levels of analytical, critical and reflective skills alongside a professional level of practical skills and knowledge. Teaching and learning on the course is underpinned by the research and scholarly activities of our experienced teaching team. On this apprenticeship you will be encouraged to take responsibility for your own learning whilst still being supported by your subject tutors. You will be encouraged to immerse yourself in the subject area. It takes 30 months full time (including six months for the EPA) and is available to students who wish to complete this course through an apprenticeship. This apprenticeship offers you the opportunity to study while being employed full time in a bioinformatics setting, enabling you to continue advancing your career as you gain a valuable postgraduate qualification.