Computational Toxicologist

**Computational Toxicologist (M/F/d) - machine learning models / biology and chemistry data/ cheminformatics/ molecular descriptors, chemical similarity, and structure-based analyses / DILI or nephrotoxicity / Python, R / using scientific computing libraries / biological pathways / English**

**Project**:
For our customer a big pharmaceutical company in Basel we are looking for Computational Toxicologist (M/F/d).

**Background**:
Are you passionate about using data and cutting-edge machine learning to improve the safety of medicines? At Roche, we are building the next generation of in silico tools to support safer and faster drug discovery. We’re looking for a Computational Toxicologist to help us develop innovative, AI-powered solutions that predict toxicological risks and translate data into actionable insights.
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..

**Tasks & Responsibilities**:

- 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.

**Must Haves**:
You’re a proactive and creative scientist who thrives at the intersection of data, biology, and chemistry. You are interested in toxicology and enjoy solving complex problems collaboratively and are driven by impact and scientific curiosity.
- 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.

**Nice to Have**:

- Experience with toxicological datasets and safety endpoints such as DILI or nephrotoxicity.
- Understanding of omics data integration or biological pathways related to toxicology.
- Familiarity with pharmaceutical R&D or prior experience in industry (a plus, but not essential).

**Reference Nr.**: 924248SDA
**Role**: Computational Toxicologist (M/F/d)
**Industrie**: Pharma
**Workplace**: Basel
**Pensum**: 100% (51% in office minimum)
**Start** : 01.07.2025 ( latest Start Date: 1.09.25)
**Duration**: 12 ++
**Deadline**: 16/06/2025

**Job Type**: 100%

Work Location: On the road