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Senior computational toxicologist - machine learning expert

Basel
beBee Careers
Inserat online seit: 15 Juni
Beschreibung

We're seeking a seasoned Computational Toxicologist to join our team.


Job Description

An exciting opportunity has arisen for a highly skilled Computational Toxicologist to design, develop and apply machine learning models to predict safety-relevant endpoints using chemical structure and biological data.

The ideal candidate will possess a solid foundation in cheminformatics and toxicology, proficient in programming languages like Python or R, and excel at collaborating and communicating complex scientific insights.

Main Responsibilities:

* Design, develop, and apply machine learning models to predict safety-relevant endpoints (e.g., liver or kidney toxicity) using chemical structure and biological data.
* Integrate chemo-informatics and in vitro safety data, with the potential to expand toward transcriptomics or other omics technologies.
* Provide in silico support for discovery and early development programs, offering scientific insights into potential safety risks.
* Leverage internal data and external knowledge bases to enhance model performance and interpretability.
* Closely collaborate with toxicologists, pharmacologists, data scientists, and chemists to co-create solutions and ensure models are meaningful and relevant.

Requirements and Qualifications:

* A PhD or MSc (with relevant experience) in Computational Toxicology, Cheminformatics, Bioinformatics, Data Science, Pharmacology, or a related field.
* Solid experience in developing machine learning models, ideally applied to chemical and biological data.
* A strong foundation in cheminformatics/chemistry, including working with molecular descriptors, chemical similarity, and structure-based analyses.
* Experience with toxicological datasets and safety endpoints such as DILI or nephrotoxicity.
* Familiarity with in vitro safety data and an interest in integrating complex biological datasets.
* Proficient in programming (e.g., Python, R) and using scientific computing libraries (e.g., RDKit, scikit-learn, Pandas, TensorFlow, or similar).
* Excellent communication and collaboration skills; able to translate technical insights for interdisciplinary teams.

Benefits and Others:

This is a great opportunity for someone who enjoys working on cutting-edge projects, applying their expertise to drive innovation, and making a tangible impact on product safety.

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