CSC3431 : Engineering Biology and AI
CSC3431 : Engineering Biology and AI
- Offered for Year: 2026/27
- Module Leader(s): Professor Jaume Bacardit
- Lecturer: Dr Harold Fellermann, Dr Gizem Buldum, Dr Jichun Li
- Owning School: Computing
- Teaching Location: Newcastle City Campus
Semesters
Your programme is made up of credits, the total differs on programme to programme.
| Semester 1 Credit Value: | 20 |
| ECTS Credits: | 10.0 |
| European Credit Transfer System | |
Pre-requisite
Modules you must have done previously to study this module
Pre Requisite Comment
N/A
Co-Requisite
Modules you need to take at the same time
Co Requisite Comment
N/A
Aims
By the end of this module students will have gained, at an introductory level, experience in, and a knowledge of:
· The basic concepts underpinning the modelling and simulation of biological systems.
· The application of computing in the design and engineering of biological systems.
· The role of artificial intelligence in supporting the whole life cycle of engineering biology.
The module will prepare interested students for a dissertation project in the research area, and potential further study or early career in the field of engineering biology. This module aims to provide a basic and
wide-ranging overview of this field, while also being adequately rigorous in its treatment and grounded in
real-world applications. The material covered is complementary to the stage 3 module (CSC3432 Biomedical Data Analytics).
Outline Of Syllabus
Students will be introduced to:
1) Fundamental cell biology.
2) Modelling and simulation of biological systems.
3) Computing based on molecules and cells.
4) Foundations of Engineering Biology.
5) Bio-design and Applied Biocomputing.
6) The role of standards in Engineering Biology.
7) AI to support decision making in Engineering Biology.
8) Generative AI for Engineering Biology.
9) Deep learning and laboratory automation for biotechnology.
Learning Outcomes
Intended Knowledge Outcomes
After completing this module students will be able to:
• Engineer simple computing systems and devices which utilise biological, ecological, and chemical processes
and techniques.
• Analyse and apply computational techniques in the development of engineered biological systems.
• Compare and select relevant approaches based on their strengths and weaknesses in applicability to practical
situations.
Intended Skill Outcomes
After completing this module students will, at a rudimentary level, be able to:
• Carry out specific literature reviews in the field.
• Analyse an engineering biology problem in order to find the most appropriate computing techniques for
supporting decision making.
• Apply Artificial Intelligence to Engineering Biology data questions.
• Apply computational approaches to the design and implementation of novel biological systems.
Teaching Methods
Teaching Activities
| Category | Activity | Number | Length | Student Hours | Comment |
|---|---|---|---|---|---|
| Guided Independent Study | Assessment preparation and completion | 30 | 1:00 | 30:00 | Lecture follow up. |
| Structured Guided Learning | Lecture materials | 20 | 1:00 | 20:00 | Lectures non-synchronous online. |
| Scheduled Learning And Teaching Activities | Practical | 12 | 2:00 | 24:00 | Practicals (in person). |
| Guided Independent Study | Project work | 40 | 1:00 | 40:00 | Practical/Lab Report 2 (2000 words). |
| Guided Independent Study | Project work | 40 | 1:00 | 40:00 | Practical/Lab Report 1 (2000 words). |
| Scheduled Learning And Teaching Activities | Drop-in/surgery | 11 | 1:00 | 11:00 | Synchronous (in person) sessions, if available. Otherwise additional synchronous online sessions - Questions re lectures. |
| Guided Independent Study | Independent study | 35 | 1:00 | 35:00 | Background reading. |
| Total | 200:00 |
Teaching Rationale And Relationship
Lectures will be used to introduce the learning material and for demonstrating the key concepts by example. Students are expected to follow-up lectures within a few days by re-reading and annotating lecture notes to aid deep learning.
This is a very practical subject, and it is important that the learning materials are supported by hands-on opportunities provided by practical classes. Students are expected to spend time on coursework outside timetabled practical classes.
Students aiming for 1st class marks are expected to widen their knowledge beyond the content of lecture notes through background reading.
Reading Lists
Assessment Methods
The format of resits will be determined by the Board of Examiners
Other Assessment
| Description | Semester | When Set | Percentage | Comment |
|---|---|---|---|---|
| Practical/lab report | 1 | M | 100 | Practical Report (maximum 3000 words) on computing and AI application to engineering biology design problems. |
Formative Assessments
Formative Assessment is an assessment which develops your skills in being assessed, allows for you to receive feedback, and prepares you for being assessed. However, it does not count to your final mark.
| Description | Semester | When Set | Comment |
|---|---|---|---|
| Practical/lab report | 1 | M | Based on practical worksheets |
Assessment Rationale And Relationship
This module focuses on a very practical subject and hence an assessment based on coursework is the best option to evaluate the student’s knowledge.
The coursework will assess the student's ability to apply the module's concepts in a practical setting and will be assessed as practical reports, which is a suitable methods for assessing the creation and application of computational bio-design tools.
Timetable
- Timetable Website: www.ncl.ac.uk/timetable/
- CSC3431's Timetable
Past Exam Papers
- Exam Papers Online : www.ncl.ac.uk/exam.papers/
- CSC3431's past Exam Papers
General Notes
N/A
Welcome to Newcastle University Module Catalogue
This is where you will be able to find all key information about modules on your programme of study. It will help you make an informed decision on the options available to you within your programme.
You may have some queries about the modules available to you. Your school office will be able to signpost you to someone who will support you with any queries.
Disclaimer
The information contained within the Module Catalogue relates to the 2026 academic year.
In accordance with University Terms and Conditions, the University makes all reasonable efforts to deliver the modules as described.
Modules may be amended on an annual basis to take account of changing staff expertise, developments in the discipline, the requirements of external bodies and partners, staffing changes, and student feedback. Module information for the 2027/28 entry will be published here in early-April 2027. Queries about information in the Module Catalogue should in the first instance be addressed to your School Office.