AI Data Scientist (Transcriptomics & cfRNA for Alzheimer's Disease Research)
Role details
Job location
Tech stack
Job description
We are seeking a visionary Staff AI Scientist to join our cell-free RNA (cf-RNA) team. This role is designed for a technical leader who can bridge the gap between advanced Generative AI/Deep Learning and the intricate biology of cf-RNA. You will drive the development of next-generation predictive and prognostic models for AD by architecting AI solutions that are fundamentally grounded in biological rigor.
The ideal candidate understands that "Garbage In, AI Out" is the primary risk in liquid biopsy. We need a scientist who can master the secondary and tertiary analysis of cf-RNA (normalization, batch correction, noise quantification) to build AI models - including, but not limited to, foundation models and Transformer-based architectures - that are robust enough for clinical-grade implementation., * AI Architecture for Genomics: Lead the design and deployment of AI/ML frameworks optimized for high-dimensional cf-RNA sequencing data to deliver clinically actionable AD insights.
- Biological Data Engineering: Develop sophisticated "AI-ready" data preprocessing workflows, including advanced methods for differential expression, batch effect mitigation, and normalization that preserve subtle biological signals.
- Model Innovation: Build and fine-tune predictive models, ranging from traditional ensembles (Survival models, Random Forest, XGBoost) to Deep Learning architectures and RNA-seq Foundation Models (LLMs) for feature extraction and zero-shot inference.
- Translational Validation: Bridge the gap between "silicon" performance and "clinical" reality by leading hypothesis-driven investigations to ensure AI outputs meet rigorous regulatory and biological standards.
- Scalable AI Pipelines: Architect end-to-end pipelines that integrate raw NGS outputs into scalable cloud-based AI feature stores, ensuring reproducibility and data governance.
- Strategic Leadership: Collaborate with wet-lab and clinical teams to translate complex AI narratives into strategic roadmaps for executive leadership.
Requirements
Do you have experience in Survival analysis?, * PhD in a Quantitative Biological Field: (e.g., Computational Biology, Bioinformatics, Applied Statistics, or Biophysics). We are looking for an "AI Scientist" who speaks the language of biology.
- 1+ Years in Biotech/Diagnostic Industry: Proven track record of taking complex NGS-based models from R&D to a validated state.
- Deep NGS Domain Expertise: Mastery of the cfRNA/mRNA-seq workflow. You must understand library prep artifacts, noise quantification, and dimensionality reduction as the "preprocessing layer" for AI.
- Advanced ML/DL Toolkit: Extensive experience with PyTorch, TensorFlow, or JAX, specifically applied to genomic datasets. Experience with multi-modal AI (integrating clinical and molecular data) is a major plus.
- Algorithmic Creativity: Ability to move beyond "off-the-shelf" libraries to develop custom loss functions or architectural tweaks that account for the unique distribution of RNA-seq count data.
- Technical Stack: Proficient in Python (the lingua franca of AI) and Linux; experience with AWS (Sagemaker, EC2) and modern software practices (CI/CD, Git).
- Scientific Mindset: A first-principles thinker who prioritizes model interpretability and biological "truth" over black-box performance metrics.
Benefits & conditions
Pulled from the full job description
- 401(k)
- Health insurance
- Paid time off
- Vision insurance
- Dental insurance
- Life insurance
- Employee assistance program, Are you ready to take the next step in your career as a Staff Data Scientist at Superfluid? We'd love to hear why you're the perfect fit for our team! Send us your resume along with a brief note on what makes you a great candidate to careers@superfluiddx.com.
Pay: $160,000.00 - $200,000.00 per year, * 401(k)
- Dental insurance
- Employee assistance program
- Health insurance
- Life insurance
- Paid time off
- Vision insurance