Are you passionate about harnessing the power of data and advanced machine learning to advance medicine safety?
This role involves collaborating with various departments to enhance drug discovery processes through in silico assessments and data-driven insights.
Please note that a strong foundation in cheminformatics and chemistry is required.
Key Responsibilities:
* Design and develop machine learning models to predict safety endpoints using chemical and biological data.
* Integrate chemoinformatics and in vitro safety data, expanding towards omics technologies.
* Provide scientific support for discovery and early development programs.
* Utilize internal and external data to improve model performance and interpretability.
* Collaborate with toxicologists, pharmacologists, data scientists, and chemists to co-create solutions.
* Contribute to efforts like biological read-across and digital workflow refinement for safety decision-making.
Requirements:
* Advanced degree in Computational Toxicology, Cheminformatics, Bioinformatics, Data Science, Pharmacology, or related field.
* Experience in developing machine learning models applied to chemical and biological data.
* Familiarity with toxicological datasets and safety endpoints.
* Proficient in programming languages such as Python or R.
* Excellent communication and collaboration skills.