The project aims at re-evaluating and improving an existing automated screening and method optimization tool (COSMOS), developed at Janssen Pharmaceutica, to aid in the task of method development for pharmaceutical samples. COSMOS has been developed to reduce the amount of trial-and-error in the method development process and base the optimization of separations on scientifically substantiated decisions. The goal of the project is to further streamline the decision-making process within COSMOS, with the aim of further reducing the time required to fully optimize a chromatographic method. This implies the redefinition and automation of a number of key decisions (e.g., selection of scouting runs) and algorithms (e.g., peak detection and peak tracking algorithms) throughout the method optimization procedure. Additionally, it will also be investigated whether COSMOS can be expanded to multi-dimensional separations.
The candidate ideally has a Master in Chemistry or Engineering, Pharmacy, Bio-informatics or Bio-engineering, with a strong interest in analytical chemistry and chemometrics.
A good knowledge of and hand-on experience with (U)HPLC are an absolute must.
The candidate is familiar with the management, analysis and interpretation of big data and has intermediate programming skills (e.g. Python, R or Matlab) for managing, analyzing and interpreting data, as well as writing their own code to solve existing data-related problems.
Candidates must be proficient in oral and written English, must have excellent communication skills, multi-tasking skills, and be team-oriented, proactive and results driven.
We offer a PhD position in a stimulating environment, wherein you will work in an internationally reputed pharmaceutical company with a strong focus on R&D and at a top European university, in well-equipped, experienced and internationally oriented research units.
You will alternate between the Department of Pharmaceutical and Pharmacological Sciences at the Gasthuisberg Campus in Leuven, Belgium and the Janssen site in Beerse, Belgium.
For more information please contact Prof. dr. Deirdre Cabooter, tel.: +32 16 32 34 42, mail: deirdre.cabooter@kuleuven.be.
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