AI Drug Development Scientists

AI Drug Discovery Scientist

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