2027 Future Talent Program - AI/ML Computational Toxicology - Intern
Core
Build and evaluate predictive models for toxicity risk and mechanistic hypotheses using multimodal pharmaceutical data (genomics, metabolomics, chemistry, in vivo/in vitro, and biomedical literature).
Role type
AI/ML Computational Toxicology Intern
Builds
Predictive toxicity models and NLP/LLM pipelines for mining unstructured reports and literature
Domain
Pharmaceutical R&D / Computational Toxicology / AI & Data Science
Deliverable
production ML models | dashboards & analysis
Required skills
Python, statistics, machine learning, data wrangling (pandas/SQL), deep learning frameworks (PyTorch/TensorFlow), Git/GitHub, NLP, LLM tools (Hugging Face, spaCy, NLTK), prompt design, fine-tuning, RAG
Preferred skills
null
Technologies
Streamlit, Hugging Face, spaCy, NLTK, PyTorch, TensorFlow, pandas, SQL
Responsibilities
Build and evaluate predictive models for toxicity risk and mechanistic hypotheses generation using multimodal pharmaceutical data; Develop NLP/LLM pipelines (prompting, fine-tuning, RAG) to mine unstructured reports and literature; Prepare dashboards and present results to scientists and leadership
Seniority
Intern
