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Graduate

MSc in Artificial Intelligence for Engineering Biology

Combining core training in AI-based and algorithmic tools for the analysis and engineering of biological systems with instruction in research topics, laboratory techniques and group project work, culminating in an individual research project and dissertation.

Full time

Open
Upcoming application deadline for 2027-28 entry:
12:00 midday UK time on Wednesday 27 January 2027

Expected length
11 months
Expected start date
11 October 2027
English language level
Higher level required

Application deadlines

12:00 midday UK time

Final application deadline for entry in 2027-28

A robotic arm in a lab

About the course

You will receive training in the foundational pillars of Artificial Intelligence (AI) based techniques (automation methodologies grounded in control theory, advanced optimisation, machine learning, and computational methods for large scale data-driven design problems). 

Foundational training in biology for postgraduate students is also available if you have a quantitative background. 

The course will equip you with the technical and computational skills necessary to apply AI tools and methods to address complex challenges in engineering biology and help prepare you for careers in industry, biotechnology and AI-driven innovation or for DPhil-level research. 

You will develop transferable skills in teamwork, leadership, communication and entrepreneurship. 

The course learning outcomes are as follows: 

  1.  Identify and interpret fundamental challenges in biology and biochemistry.
  2. Analyse and apply advanced feedback control mechanisms, AI and machine learning techniques, data-driven algorithms and advanced statistics.
  3. Examine and contrast machine learning tools with stochastic biological and biochemistry problems.
  4. Evaluate and optimise synthetic circuits and bioprocesses.
  5. Design and implement quantitative engineering biology in practice.
  6. Communicate, collaborate and show effective leadership to address complex challenges in engineering biology.  
  7. Design and conduct an individual research project in an appropriate area of artificial intelligence for engineering biology.

Course structure

This section provides an overview of the course structure, while details of the individual course components are provided below.

Core modules are delivered through lectures, classes, research seminars, laboratory work and demonstrations, group project sessions, and optional drop-in classes. 

During your first term, you will study two core modules: Theory and Algorithms, and Methods, Modelling and Implementation. These modules will continue in the second term, during which time you will also work on your group project. In the third term and over the summer, you will complete your individual research project.

Approximately half of the course is delivered in the form of lectures and whole-cohort research seminars. You will also participate in laboratory work, including demonstrations, and group project sessions. Classes and laboratory work are delivered to groups of students. You can expect to spend at least 30 hours on the course each week; during term time, approximately half of that will be contact time in the form of lectures, classes, laboratory work and group project sessions. The remainder of your time will be spent on self-directed work, including preparatory reading and working on assessments.

You will be required to attend an in-person research 'poster conference' in Oxford in June. 

Core components

You will take five core modules and submit a dissertation. 

Course details

Entry requirements

For entry in 2027-28

Funding and costs

College preference

Before you apply

Completing your application

Contact details