Job Description

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.
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..
The ideal candidate is a proactive and creative scientist with a PhD or MSc in a relevant field, boasting strong experience in machine learning applied to chemical and biological data. They possess a solid foundation in cheminformatics and toxicology, are proficient in programming languages like Python or R, and excel at collaborating and communicating complex scientific insights. This individual is driven by curiosity and a desire to make an impact by solving challenging problems at the intersection of data, biology, and chemistry..
Tasks & 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.

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.:SDA
Role: Computational Toxicologist (m/f/d)
Industrie: Pharma
Workplace: Basel
Pensum: 100% (51% in office minimum)
Start :( latest Start Date:)
Duration: 12 ++
Deadline: 16/06/2025
If you are interested in this position, please send us your complete dossier via the link in this advertisement. If this position does not fit your profile and you wish to be considered for another position directly, you can also send us your dossier via this ad or to jobs[at]itcag[dot]com.
Contact us for more information about our company, our positions or our attractive Payroll-Only programme:
About us:
ITech Consult is an ISO 9001:2015 certified Swiss company with offices in Germany and Ireland. ITech Consult specialises in the placement of highly qualified candidates for recruitment in the fields of IT, Life Science & Engineering.
We offer staff leasing & payroll services. For our candidates this is free of charge, also for Payroll we do not charge you any additional fees. jid3a3794ea jit0624a jiy25a