Job Description

We are seeking a highly accomplished

Senior Oncology Computational Biologist

to lead innovative approaches that support both Lantern's internal drug development programs and external-facing partnerships. You will drive strategic direction for AI-enabled oncology drug discovery and have the opportunity to work with cutting-edge teams advancing precision cancer medicine.

The ideal candidate will demonstrate orthogonal thinking in drug discovery and development, with proven ability to match right drugs to the right indications with bioinformatics and AI.

RESPONSIBILITIES:

Lead the strategic expansion, selection, and application of datasets and AI/ML tools, integrating public and proprietary preclinical and clinical results to elucidate molecular mechanisms of action (MOA) and therapeutic potential Direct cross-functional teams in analyzing complex genomic contexts of cancer biological pathways to optimize MOA-indication matching and therapeutic strategies Define biomarker discovery strategies by integrating MOA, therapeutic potential, and cancer genomics to enhance molecular selectivity Guide medicinal chemistry efforts by interpreting chemical and structural features to enable developmental modifications for NCEs with improved PK and efficacy profiles Uncover novel therapeutic applications of existing molecules through AI-driven analysis of drug response pathway interactions Synthesize insights from diverse preclinical data sources (internal and external) to inform optimal combination therapy strategies Pioneer AI strategies for novel cancer drug targeting approaches, including ADCs, multispecific antibodies, and emerging modalities Oversee development and maintenance of in silico molecule pipelines and infrastructure supporting AI/ML-driven bench projects Collaborate with clinical and preclinical research teams to architect proof-of-concept study designs Provide scientific leadership and mentorship to AI drug development teams

REQUIRED QUALIFICATIONS:

7+ years of experience in AI-directed drug development environments with demonstrated impact on drug candidate advancement 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) Strong publication record and proven grant writing success in AI-based drug development Deep expertise in matching ML-based in silico discovery of cancer drug response pathways and biomarkers to biological relevance Advanced proficiency in deciphering MOA from complex genomic studies (CRISPR, RNAi, perturbation screens) and applying AI to optimize drug development strategies Comprehensive knowledge of genomic and cancer pathway databases with track record of leveraging diverse public biomedical resources Proven experience in drug candidate prioritization and portfolio decision-making in biopharmaceutical settings Exceptional communication skills with ability to influence diverse stakeholders through written and oral presentations Strong programming proficiency (Python, R, or similar) Demonstrated leadership in building, managing, and scaling distributed AI-focused scientific teams

PREFERRED QUALIFICATIONS:

Experience with cloud computing platforms (AWS, GCP, Azure) for large-scale biological data analysis Track record of IND filings or clinical trial contributions Industry partnerships or business development experience
Job Type: Full-time

Work Location: In person