Job Description

Posted on 06 October 2022

Group: CAMP

Project Overview

Cell therapy is an emerging clinical approach with the potential to treat a range of illnesses and medical conditions. However, the critical bottlenecks for a successful clinical outcome is ensuring consistent manufacturing of cell therapy products with well established critical quality attributes (CQA). In SMART-CAMP, we have developed novel microfluidic imaging and spectroscopy technologies to probe the cellular attributes of the T-cells and stem cell products. The deployment of the technologies to a clinical or industry setting would require development of machine learning (ML) models of real-time imaging data to establish a database of cellular characteristics with correlation to cell therapy function, phenotype and/or potency. The optimised ML will be packaged into an automation application programme interface for integration into a process analytical technology for advanced cell manufacturing in bioreactors.



This is a Research Engineer role which will focus on the development of machine learning models and deployment of CAMP technologies as PAT in cell manufacturing. The candidate is expected to work with biologist and engineers to understand the label-free technologies and cell manufacturing workflows for effective machine learning development.

The ideal candidate should be skilled in coding, and software development, and proficient in Python, Tensorflow or Pytorch, large-scale sequential-data analysis (including time series), neural networks.

• Implement data analytical projects involving image processing for immune cells or stem cells.
• Manage the image and spectroscopy database with proper records for logging and metadata of experiments.
• Develop machine learning models in correlation to established CQAs such as cell viability, potency and metabolism
• Deployment of machine learning models for software user-interface, automation and bioreactor PAT integration.
• Assist in routine maintenance of laboratory equipments, consumables and SOPs where needed.

Job Requirements

• Bachelors degree in Computer Science, Applied Mathematics, Electrical Engineering, Physics or other related disciplines are encouraged to apply.
• Good data analytical skills and python coding is considered a plus. Prior background in coding language is required.
• Proficient in python coding and data preparation with basic experience in deploying machine learning models (e,g, DNN, CNN, SVM).
• Applicants that have just completed an undergraduate degree and have an interest in pursuing postgraduate and/or doctoral studies later are also strongly encouraged to apply.

Interested applicants are invited to send in their full CV/resume, cover letter and list of two references (to include reference names and contact information). We regret that only shortlisted candidates will be notified.