Sr. Bioinformatics Scientist - AI/ML for Multimodal Precision Medicine

Job summary

We are seeking a highly motivated Senior Bioinformatics Scientist with expertise in imaging and multi-omics data analysis to contribute to AI/ML model development, validation, and deployment. You will join a multidisciplinary team of scientists and engineers working at the intersection of biology, computation, and clinical research.

Responsibilities

• AI/ML Development: Design, train, and validate machine learning models for analyzing digital pathology (whole-slide images), genomics, and multi-modal data to predict biomarkers, therapeutic response, and clinical outcomes.

• Data Integration: Build and optimize pipelines that integrate DNA/RNA sequencing, histopathology, imaging, immune profiling, and clinical metadata into unified AI-ready datasets.

• Model Validation and Deployment: Perform analytical and clinical validation of AI/ML algorithms and integrate them into research and production workflows.

• Data Curation and Annotation: Manage and preprocess large-scale datasets, including image annotation and omics data harmonization, ensuring data quality and usability.

• Collaboration: Work closely with pathologists, computational scientists, biologists, and software engineers to design translational solutions that address real-world clinical challenges.

• Biomarker Discovery: Support identification of biomarkers from histopathology, spatial omics, and transcriptomic data to enable patient stratification and companion diagnostics.

• Research and Innovation: Stay current with the latest advancements in AI, digital pathology, spatial biology, and foundational models to contribute to innovation pipelines and publications.

Qualifications

Required Qualifications

• PhD (or MS with 2+ years of relevant experience) in Computational Biology, Bioinformatics, Computer Science, AI, or related field.

• Strong background in machine learning, including deep learning (CNNs, ViTs, UNet), optimization, and self/weakly-supervised learning.

• Proven experience in developing AI models for medical imaging (classification, segmentation, detection) and handling large-scale WSI datasets.

• Solid knowledge of omics data processing (e.g., RNA-seq, WES/WGS), preferably in oncology or immunology settings.

• Proficiency in Python and AI/ML frameworks (e.g., PyTorch, TensorFlow).

• Excellent problem-solving skills, especially for multi-modal data integration.

• Strong communication and collaboration skills; experience working in interdisciplinary teams.

• A track record of publications, patents, or contributions to deployed AI tools in healthcare.

Preferred Qualifications

• Experience with foundational model architectures and multi-modal model training.

• Hands-on experience with histopathology, spatial omics, or structured/unstructured clinical data.

• Previous work in a biotech, clinical research, or regulated environment.

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