Job Description

The Life Science Career Network
CTC are specialised industry experts who can help companies source the best talent and provide reliable HR and consulting services, support varied candidates in finding promising career opportunities and offer the latest in skill development training programmes.
Our client is a pioneer in Drug Discovery and Development and one of the frontrunners in Personalised Healthcare. As the world's largest R&D spender in the pharmaceutical and diagnostics domain, they work in a vast number of drug discovery & therapeutic areas and are highly recognized internationally. A leader in the field of both in vitro diagnostics and manufacturing and selling of several innovative drugs.
We are currently looking for an enthusiastic Computational Toxicologist for a 12-month contract based in Basel, Switzerland.
This is your opportunity to be part of a highly interdisciplinary team that bridges cheminformatics, data science, toxicology, and drug development. You will apply state-of-the-art machine learning to address critical safety questions and actively contribute to the integration of diverse data types-including chemical structures, in vitro assay data, and evolving omics readouts.
In addition to model development, you will work closely with discovery project teams to provide in silico safety assessments and scientific support. You'll help reuse historical data to inform current programs and collaborate with colleagues across departments to identify pain points and develop impactful solutions.
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 chemoinformatics 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.
• Collaborate closely with toxicologists, pharmacologists, data scientists, and chemists to co-create solutions and ensure models are meaningful and relevant.
• Contribute to broader efforts such as biological read-across, reverse translation of historical data, and refinement of digital workflows for safety decision-making.

Qualifications and Experience:

• Relevant working/residency permit or Swiss/EU-Citizenship required
• 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.
• 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.

Would you like to learn more about CTC and the opportunity outlined? Please, get in contact with us: you may either use the 'apply now' button, or write an email to us, or reach out to us on the phone.