ph3The Swiss Centre for Applied Human Toxicology (SCAHT), associated to the University of Basel, is seeking a highly motivated bPostdoctoral Researcher in Digital Computational Toxicology /b 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. /h3 pDeadline for application: August 16, 2026 /p pStart of position: to be agreed upon /p h3Your position /h3 ul liDevelop and implement FAIR-compliant data management strategies, standards and data management plans. /li liBuild, curate and maintain toxicological datasets and digital knowledge resources from public databases, scientific literature, omics datasets and regulatory resources. /li liDevelop and apply computational methods for analysing, integrating and visualising complex toxicological datasets. /li liEvaluate, implement and further develop AI- and machine learning-based approaches for data curation, analysis and knowledge extraction. /li liDevelop and integrate Adverse Outcome Pathways (AOPs) and other mechanistic knowledge frameworks to support biology-informed risk assessment. /li liContribute to national and international collaborative research projects and grant proposals. /li liPublish scientific results in leading peer-reviewed journals and present findings at international conferences. /li liSupport training activities, knowledge transfer and collaboration within the academic, regulatory and industrial landscape. /li /ul pbDuration: /b 2 years with the option of prolongation. /p pbStart: /b As per agreement. /p h3Your profile /h3 pWe welcome applications from highly motivated researchers with a strong background and passion for computational and data-driven toxicology. /p h3Essential qualifications /h3 ul liPhD in Toxicology, Computational Toxicology, Data Science, Bioinformatics, Computational Biology or a related discipline. /li liDemonstrated expertise in toxicology, or a strong interest in applying computational methods to toxicological research. /li liExperience in computational data analysis using Python and/or R, including the handling, curation and integration of large biological or toxicological datasets. /li liExperience in handling, curating and integrating large biological or toxicological datasets. /li liKnowledge of database management, FAIR data principles and data governance. /li liExcellent analytical and problem-solving skills. /li liExcellent written and spoken English with strong communication skills. /li /ul h3Desirable qualifications /h3 ul liExperience with machine learning, artificial intelligence and/or natural language processing. /li liExperience with reproducible computational research using tools such as Git, Docker and workflow management systems. /li liFamiliarity with public toxicological databases (e.g. AOP-Wiki, ToxCast, PubChem or ChEMBL). /li liA track record of scientific publications. /li liKnowledge of German and/or French. /li /ul h3We offer you /h3 ul liThe opportunity to shape the emerging field of Digital Toxicology. /li liAn internationally visible and collaborative research environment. /li liClose collaboration with academic, industry and regulatory partners at national and international levels. /li liAccess to state-of-the-art computational, AI and toxicological research infrastructure. /liliOpportunities to develop innovative digital solutions supporting the regulatory implementation of New Approach Methodologies (NAMs). /li liExcellent opportunities for scientific and professional career development. /li liFlexible working arrangements and employment in Basel, Switzerland, based on the terms of the University of Basel. /li /ul h3Application / Contact /h3 pPlease send your application as one PDF including motivation letter, CV and work experience via Email to /p pFor further information, please consult our website scaht.org and/or contact our scientific coordinator Dr. Stéphanie Boudon, Email : or Dr. Lothar Aicher, Email: /p /p #J-18808-Ljbffr
Post-Doctoral Research Position (80–100%) in Digital & Computational Toxicology Arbeitgeber: Universität Basel
Die Universität Basel ist ein hervorragender Arbeitgeber, der seinen Mitarbeitenden eine langfristige Perspektive in einem stabilen und zukunftsorientierten Umfeld bietet. Mit einer sorgfältigen Einarbeitungsphase und kontinuierlichen Weiterbildungsmöglichkeiten fördert die Universität aktiv das Wachstum ihrer Angestellten. Die offene und serviceorientierte Arbeitskultur ermöglicht es Ihnen, direkt mit Dozierenden und Veranstaltenden zusammenzuarbeiten und Ihre technischen Fähigkeiten in einem internationalen und dynamischen Team weiterzuentwickeln.
