Post-Doctoral Research Position (80–100%) 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. Duration: 2 years with the option of prolongation. Start: As per agreement.

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.

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.