Job Description

The Characterization and Materials Sciences (CMS) department seeks improvements in data analysis and visualization. The candidate will help configure machine learning algorithms for analysis and assist in developing R Shiny applications for visualization.

The candidate will set up and optimize automation platforms, primarily automated liquid handlers (ALH) for automated sample preparation across analytical methods. Responsibilities include scripting for the liquid handlers and testing these scripts in the lab, initially with water and later with actual samples.

Within UCB's CMC division, the Characterization and Materials Sciences (CMS) department, in collaboration with other departments, has decided to implement a single cloud-based Electronic Laboratory Notebook (ELN). This strategic decision means that the teams have to develop a set of ELN templates and workflows that allows the various analytical methods used at CMS in Slough to be effectively tracked, coded and integrated into the new ELN.

In an analytical laboratory for Biomolecules under good laboratory practice conditions, the candidate will be responsible for developing ELN templates for different analytical methods and connecting laboratory equipment to the ELN.

The person will need to ensure that the new ELN templates are consistent with those already developed by other departments. He/she will need to check with users to ensure that the ELN templates are consistent with the practical steps performed in the laboratory and ensure everything is "user friendly". In addition, the student will be responsible for integrating the various laboratory instruments into these ELN-templates.

The student will ensure the robustness of these ELN templates by demonstrating that they always work in the same way, thus allowing the harmonization of working procedures between people and laboratories.