Sciome consults with leading researchers across the globe, providing advanced analytics and computational modeling support for studies that generate large volumes of scientific data across health, toxicology, and environmental domains. We are seeking a Computational Toxicologist to join our growing team to support a diverse range of projects aimed at understanding the effects of chemical, environmental, or therapeutic exposures on biological systems.
Our clients leverage high-throughput screening technologies and generate vast multi-dimensional datasets. These projects require rigorous computational approaches, including toxicokinetic modeling, cheminformatics, and systems toxicology techniques. We collaborate with our clients to develop and implement novel predictive models, machine learning algorithms, and software tools—often contributing to peer-reviewed publications and open-source packages.
The selected candidate will work closely with leading scientists across disciplines, contributing to impactful public health and regulatory decision-making. This is a unique opportunity for a scientist interested in cutting-edge computational methods and their application to real-world toxicological problems.
Education
Master’s or PhD degree in Toxicology, Computational Biology, Bioinformatics, Computer Science, or a closely related field.
Key Responsibilities
- Develop and implement high-throughput toxicokinetic (HTTK), PBPK, and systems biology models.
- Design, develop, and apply computational risk assessment models based on hazard and exposure.
- Develop and evaluate mechanistic based toxicity assessment such as Adverse Outcome Pathways (AOPs), quantitative AOPs, Integrated Approaches to Testing and Assessment (IATA) or Defined Approaches (DA).
- Collaborate in the analysis of large toxicogenomic, transcriptomic, or high-content screening datasets using machine learning and statistical methods.
- Ensure robustness, transparency, and scientific validity of modeling approaches used across projects.
- Assist in scientific reporting, manuscript preparation, and development of technical documentation.
Desired Skillset
The ideal candidate will have experience in several of the following areas:
- Strong foundation in toxicology, computational modeling, and data analytics.
- Experience with HTS/HTTr data, ToxCast/Tox21, and Adverse Outcome Pathways (AOPs).
- Familiarity with modeling tools such as HTTK, PBPK, OpenGEMS, or relevant R/Python packages.
- Proficiency in statistical and machine learning techniques applied to biological data.
- Programming experience in R and/or Python;.
- Demonstrated ability to interpret complex biological datasets and communicate findings clearly.
- Strong communication and writing skills in English are essential.
How to Apply
- Send your detailed CV via email to jobs@sciome.com.
- Refer to the position title Computational Toxicologist.
- Provide accurate contact information.
