(Seoul) Biomedical Data Scientist · Precision Oncology - 전문연 가능

"Conquering cancer through AI" Lunit, a portmanteau of ‘Learning unit,’ is a medical AI software company devoted to providing AI-powered total cancer care. Our AI solutions help discover cancer and predict cancer treatment outcomes, achieving timely and individually-tailored cancer treatment.

🗨️ About the Team Lunit’s portfolio includes AI algorithms that analyze medical images—such as digital pathology, CT, mammography, and chest X-rays—to support cancer detection and treatment decisions. With 200+ publications and abstracts, 100+ research partnerships with leading institutions, and multiple FDA-cleared AI solutions, Lunit is at the forefront of medical AI. Lunit is organized into two specialized groups aligned to our mission: • Cancer Screening Group: Focused on early and accurate cancer detection, primarily through radiology analysis. • Oncology Group: Focused on understanding cancer biology to optimize treatment planning, currently with an emphasis on digital pathology. As our mission evolves, we will continue expanding data modalities to further enhance cancer care.

🗨️ About the Position We are seeking a Biomedical Data Scientist to join our Oncology Group. This role focuses on the hands-on analysis of multi-modal biomedical and clinical data to drive the development and validation of AI-powered biomarkers. Working at the intersection of technology and medicine, you will collaborate with clinicians, AI researchers, and engineers to build solutions that improve treatment selection for cancer patients. This position offers the opportunity to contribute to high-impact projects conducted in partnership with leading academic medical centers and global pharmaceutical organizations. The ideal candidate will possess a strong foundation in cancer biology, a genuine interest in the application of medical AI, and the analytical problem-solving skills necessary to navigate complex datasets and research challenges. 

🚩 Roles & Responsibilities • Perform data analysis to validate AI-derived biomarkers in precision oncology. This involves handling clinical data (e.g. survival analysis) but also paired genomic/medical imaging datasets • Collaborate with the AI research team to evaluate the clinical performance of our algorithms, identifying strengths and areas for improvement. Actively involved in shaping the direction of our AI model improvement projects • Conducting internal and external collaborative research, publishing results at major conferences (ASCO, ESMO, AACR) and journals.