Senior Translational Scientist
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Job Description
Senior Translational Scientist advancing oncology biomarkers and treatment-response prediction. Translating Bioptimus’ biomedical AI foundation models into patient-care discoveries.
Responsibilities:
- Investigate clinical, histopathological, and spatial transcriptomics data across the Bioptimus data corpus to study tumor biology
- Discover novel biomarkers predictive of treatment response or resistance
- Shape Bioptimus' R&D mission to learn the dynamics of human biology
- Guide model development and interpretability and design features relevant to clinical outcomes
- Collaborate with the Clinical Data Manager to keep data linked to intended discoveries
- Stay up-to-date with oncology and immunology modalities and clinical decision-making developments
- Present a translational research panel talk to AI researchers and computational biologists
- Potentially complete a technical assessment
- Collaborate with hospitals, biobanks, researchers, and engineers globally
Requirements:
- Advanced clinical/science degree (PhD, PharmD, MD), e.g. in cancer biology, molecular biology, genomics, or a related field; alternatively, MD with a strong oncology background and exposure to computational concepts
- Strong understanding of cancer biology, tumor evolution, immune microenvironment, therapeutic mechanisms, response/resistance biology, and patient outcomes
- Solid understanding of clinical trials and oncology drug development
- Experience analyzing biological samples for biomarker discovery and personalized treatments
- Excellent communication skills and willingness to work collaboratively with AI researchers and computational biologists
- Preferably deep expertise in colorectal cancer or lung cancer, with related project experience
- Familiarity with clinical, medical, pharmaceutical, or biotechnology environments
- Track record of lead-author publications in cancer biology or oncology at high-impact journals
- Experience with at least one modality: H&E, bulk-RNAseq, spatial transcriptomics, spatial proteomics, single-cell RNA-seq, or high-content/pooled perturbation screens
- Ability to leverage Python and reproducible computational workflows to analyze complex, longitudinal clinical datasets
- Experience or prior knowledge of small molecules, nucleic acids, peptides, enzymes, antibodies, cell therapies, and stem cell treatments
- Familiarity with clinical trial governance and healthcare policies
- CV submitted in English
Benefits:
- Competitive salary and equity package
- Flexible work arrangements, including remote options
- Opportunities for professional growth and leadership development
- Collaborative and mission-driven work environment
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