The Swiss Centre for Applied Human Toxicology (SCAHT), associated to the University of Basel, is seeking a highly motivated Postdoctoral Researcher in Digital & Computational Toxicology to strengthen SCAHT's activities in digital transformation of human-relevant and regulatory toxicology to next-generation risk assessment. We are looking for a scientist with strong background in toxicology and expertise in computational toxicology, data science, artificial intelligence and data governance. Ideally, the candidate has experience in applied science or a keen interest in applying their experience to applied research goals and questions. The successful candidate will contribute to the development of innovative digital infrastructures, computational workflows and AI-enabled tools that support the national and international toxicology community.
Deadline for application: August 16, 2026
Start of position: to be agreed upon
Your position
- Develop and implement FAIR-compliant data management strategies, standards and data management plans.
- Build, curate and maintain toxicological datasets and digital knowledge resources from public databases, scientific literature, omics datasets and regulatory resources.
- Develop and apply computational methods for analysing, integrating and visualising complex toxicological datasets.
- Evaluate, implement and further develop AI- and machine learning-based approaches for data curation, analysis and knowledge extraction.
- Develop and integrate Adverse Outcome Pathways (AOPs) and other mechanistic knowledge frameworks to support biology-informed risk assessment.
- Contribute to national and international collaborative research projects and grant proposals.
- Publish scientific results in leading peer-reviewed journals and present findings at international conferences.
- Support training activities, knowledge transfer and collaboration within the academic, regulatory and industrial landscape.
Duration:2 years with the option of prolongation.
Start:As per agreement.
Your profile
We welcome applications from highly motivated researchers with a strong background and passion for computational and data-driven toxicology.
Essential qualifications- PhD in Toxicology, Computational Toxicology, Data Science, Bioinformatics, Computational Biology or a related discipline.
- Demonstrated expertise in toxicology, or a strong interest in applying computational methods to toxicological research.
- Experience in computational data analysis using Python and/or R, including the handling, curation and integration of large biological or toxicological datasets.
- Experience in handling, curating and integrating large biological or toxicological datasets.
- Knowledge of database management, FAIR data principles and data governance.
- Excellent analytical and problem-solving skills.
- Excellent written and spoken English with strong communication skills.
Desirable qualifications- Experience with machine learning, artificial intelligence and/or natural language processing.
- Experience with reproducible computational research using tools such as Git, Docker and workflow management systems.
- Familiarity with public toxicological databases (e.g. AOP-Wiki, ToxCast, PubChem or ChEMBL).
- A track record of scientific publications.
- Knowledge of German and/or French.
We offer you
- The opportunity to shape the emerging field of Digital Toxicology.
- An internationally visible and collaborative research environment.
- Close collaboration with academic, industry and regulatory partners at national and international levels.
- Access to state-of-the-art computational, AI and toxicological research infrastructure.
- Opportunities to develop innovative digital solutions supporting the regulatory implementation of New Approach Methodologies (NAMs).
- Excellent opportunities for scientific and professional career development.
- Flexible working arrangements and employment in Basel, Switzerland, based on the terms of the University of Basel.
Application / Contact
Please send your application as one PDF including motivation letter, CV and work experience via Email to angela.duarte@unibas.ch.
For further information, please consult our website scaht.org and/or contact our scientific coordinator Dr. Stéphanie Boudon, Email : stephanie.boudon@unibas.ch or Dr. Lothar Aicher, Email: lothar.aicher@unibas.ch
