Offre de thèse à l'Université de Liege

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Edité le 22/08/2018

Le groupe de recherche ANALOG recrute un doctorant pour une thèse à l'Université de Liege:

For a multidisciplinary project in collaboration with the Free University of Brussels, Ghent University and the University of Liège focusing on Mining Chemical Data in Complex Samples, the ANALOG research group of the University of Liège (ULiege) is looking for a highly motivated PhD candidate.

The PhD position will be co-promoted by Profs. Marianne Fillet and Philippe Hubert. Prof. Marianne Fillet mainly works on the development of innovative and robust analytical methods (DoE and validation) for the separation and quantitation of (bio)pharmaceuticals in GMP environment and disease biomarkers in complex matrix (cells, tissues, biological fluids). Over the last 15 years, Fillet's research group focuses more particularly on capillary electrophoresis, UHPLC and nano-LC hyphenation with different kinds of mass spectrometers (IT, TQ, IMS-Q-TOF). Prof. Hubert is currently working on risk-based strategy for the robust development and optimization of ultra-high performance liquid chromatography (UHPLC) and supercritical fluid chromatography (SFC) methods in combination with simple quadrupole mass spectrometry (MS) for pharmaceutical analysis as well as counterfeit or poor quality medicines. Recently, his group has initiated an innovative strategy to combine optimization and validation steps on the framework of analytical quality-by-design (AQbD) strategy allowing a systematic and scientific approach of the entire analytical method lifecycles.

Project

The PhD researcher will work on building predictive model of the sample constituents to simulate chromatograms and electropherograms under various conditions and in combination of different modes. This concept has already been reported both for mono- and multi-dimensional RPLC separations using the well-established linear solvent strength model. However, other emerging and orthogonal chromatographic modes, involving a multimodal retention mechanism, require more complex retention models. A multidimensional modeling and optimization approach will be considered in other to reach maximal peak capacity. The definition of an optimal set of scouting runs for combination chromatographic modes will be investigated using a comparative in silico test. Results obtained by in silico test will be tested in collaboration with other PhD involved in the project. The developped algorithm will be tested on (bio-)pharmaceuticals (synthetic drugs, protein and oligonucleotide-based therapeutics) and biological applications (complex proteomic samples) using different chromatographic and electrophoretic combinations coupled with UV or MS/MS detection.

Profile

The candidate ideally has a Master in Bioinformatics, Bioengineering, Chemistry, Statistics or Pharmaceutical Sciences, with a strong interest in analytical chemistry and computer sciences. The candidate is familiar with experimental testing as well as chemometrics in the framework of establishment of predictive models. Good algorithm programming skills would be an asset. 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. The candidate will work as a member of a large research project that will involve frequent interactions with external researchers.

The position can start immediately for 4 years (2+2) period. Interested candidates should send their CV and a motivation letter to following email address:           

                                                                                                    

Offer

The Center for Interdisciplinary Research on Medicine (CIRM) offers a PhD position in a stimulating environment at a top European university in a well equipped, experienced and internationally oriented research unit. You will be based at Department of Pharmacy at the Centre Hospitalier Universitaire (CHU) Campus in Liège.

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