We are looking for an experienced Physiologically-based pharmacokinetic (PBPK) modeler post-doctoral researcher to join ProtoQSAR in a 3-year Torres Quevedo contract.
The aim of the candidate will be to develop computational PBPK predictive models for bioactive compounds, mainly drugs.
ProtoQSAR–MolDrug is specialized in the design, optimization, valorization, and development of new compounds (small molecules, peptides, nanomaterials, mixtures…) through Machine Learning-powered chemoinformatics and structural bioinformatics (QSARs, molecular docking, molecular dynamics, etc.). Our tools allow for the prediction and assessment of physicochemical, biological, pharmacological, and/or (eco)toxicological properties of substances.
We work in chemistry, regulatory toxicology, compound discovery, and development (biotech, pharma, veterinary, cosmetics, nutraceuticals, agrifood…). We have experience in 10+ international research projects and 25+ projects, and our team has 80+ publications on our topics of interest.
- To manage and carry out an independent research project in close collaboration with the ProtoQSAR-Moldrug staff and collaborators
- To actively participate in research and training activities within the ProtoQSAR’s and Moldrug’s group
- To disseminate research results in the scientific community (via international conferences) and in the non-scientific community (via outreach and public engagement)
- Support high impact product development projects in all stages of drug development using mechanism and physiologically-based PK/PD modeling and simulation methodologies, including QSP modelling, physiological based pharmacokinetic (PBPK) modeling, disease progression modelling and model-based landscape analysis, etc.
- PhD in Chemistry, Pharmacology, Toxicology or a relateddiscipline
- Extensive knowledge and interest in the areas of PK modeling, PKPD modeling, and systems pharmacology modeling
- Good track record of early achievements, including significant publications as main author in major international peer reviewed scientific journals
- Basic understanding of in silico modeling and machine learning algorithms
- Experience in programming (python / Java)
Person specifications and qualities
- Strong analytical and problem-solving skills
- Ability to logically conceptualize and summarize the research findings
- Excellent verbal and writing communication skills
- Ability to interact with colleagues and staff and to communicate complex information clearly
- Ability to organize resources, manage time and meet deadlines
How to apply
If interested, please send Curriculum Vitae, a letter of motivation and two-three recommendation letters to firstname.lastname@example.org before Monday 7th February 2022.