25/07/2019
Development of advanced models for chemical safety endpoints
Job Description
The candidate will be in charge of applying state-of-the-art machine learning methods for the prediction of chemical safety endpoints, as well as developing novel methodologies for the integrated assessment of uncertainties associated to the predictions.
Project and Institution that finance the contract: The work is supported by grant: PR02717 - H2020-JTI-IMI2-2016- eTRANSAFE M.PASTOR
Skills and Experience
A degree or master in Biology, Bioinformatics or related disciplines. Good communication skills in English. Experience in handling chemical safety data. Experience in the development of predictive models for biological endpoints. Good programming skills in Python and/or R
Benefits of the opening
Initially a full-time position for 12 months will be offered, 37,5 hours/week, which can be renewed for a period open to discussion.
Information on the application process: Send CV and letter of interest, to carina.oliver@upf.edu (REF: MP_eT )
Deadline: Sept 15th, 2019
Contact: Carina Oliver, Management - Research Programme on Biomedical Informatics (GRIB, IMIM/UPF)