The current regulation on chemical substances makes it necessary to consider toxicological risks more widely in
energy materials and they are gradually becoming a selection criterion for formulations.
The project concerns the development of a tool for rational molecular design and toxicological evaluation of energy
The postdoctoral position will be structured in different steps:
– From raw formulas of compounds, thousands of 3D structures will be generated and filtered according to
– The first prediction filters will be dedicated to toxicology and eco-toxicology will be developed in the
laboratory using QSAR techniques or machine learning algorithms.
– The development of new filters will be explored in order to design new pharmacophoretic approaches.
– The work will be done at high throughput to be as exhaustive as possible and will require the scripting of
The candidate will have completed his or her doctoral thesis in the field of bioinformatics or chemo-informatics
and will have skills in algorithmic and development. Experience in the field of statistics, QSAR, or machine
learning will be appreciated.
The successful candidate will be hire by the CNES and the salary will be determined in function of the CNES grid.
The position is in Lyon, France.
Duration : 1 year
Beginning : September 2018
Deadline : March 25th 2018.
Town : Lyon, France.
Laboratory : Equipe Prabi-LG / LBTI UMR N°5305 CNRS UCBL
Contact : firstname.lastname@example.org
Group leader PRABI-LG
7 Passage du vercors, 69367 Lyon cedex 07, FRANCE