Job Description

We are seeking talented and highly motivated

AI Drug Discovery Scientists

to develop innovative approaches supporting Lantern's internal drug development pipeline and external partnerships. You will work alongside cutting-edge teams in oncology drug development to accelerate the path from target to therapy.

The ideal candidate will bring innovative thinking to shift paradigms in drug discovery and development, with passion for matching right drugs to right indications faster and more cost-effectively.

RESPONSIBILITIES:

Contribute to expanding, selecting, and appropriately applying datasets and AI/ML tools, integrating public and proprietary preclinical and clinical results to understand MOA and therapeutic potential Analyze complex genomic contexts of cancer biological pathways to inform optimal MOA-indication matching strategies Investigate relationships between MOA, therapeutic potential, and cancer genomics to identify biomarkers enhancing molecular selectivity Evaluate chemical and structural features of molecules to support developmental modifications for NCEs with improved PK and efficacy Uncover therapeutic potential of existing molecules using AI-driven analysis of drug response pathway interactions Extract actionable insights from preclinical internal and external data sources to guide optimal combinatorial strategies Apply AI methodologies for novel targeting of cancer drugs including ADCs and other targeted modalities Build and maintain in silico molecule pipelines and infrastructure feeding AI/ML drug discovery bench projects Collaborate with clinical and preclinical research teams to support proof-of-concept study designs Contribute to scientific publications and grant applications

REQUIRED QUALIFICATIONS:

3+ years of experience working in AI-directed drug development environments Ph.D. in Computational Biology, Bioinformatics, Computational Chemistry, Cancer Biology, or related field (Bachelor's or Master's degree with exceptional experience will also be considered) Publication record in AI-based drug development Demonstrated skills in matching ML-based in silico discovery of cancer drug response pathways and biomarkers to biological relevance Working knowledge of deciphering MOA from complex genomic studies (CRISPR analysis, genetic screens) and utilizing AI for drug development strategy Knowledge of genomic and cancer pathway data sources with experience utilizing diverse public biomedical databases for drug response interrogation Experience in drug candidate prioritization within biopharmaceutical settings Strong communication skills for preparing and presenting scientific data to diverse audiences Proficiency in programming languages (Python, R, or similar)

PREFERRED QUALIFICATIONS:

Experience with grant writing Team leadership or project management experience Familiarity with remote/distributed team collaboration
Job Type: Full-time

Work Location: In person