Post-Doctoral Research Position; –in Digital & Computational Toxicology

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

• 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.

We welcome applications from highly motivated researchers with a strong background and passion for computational and data-driven toxicology.

• 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.

• 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, Tox Cast, Pub Chem or ChEMBL).
• A track record of scientific publications.
• Knowledge of German and/or French.

• 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.

Please send your application as one PDF including motivation letter, CV and work experience via Email to angela.duarte.

For further information, please consult our website scaht.org and/or contact our scientific coordinator Dr. Stéphanie Boudon, Email : stephanie.boudon or Dr. Lothar Aicher, Email: lothar.aicher