Improve the performance of industry standard emotion detection models on people of color
Design a patient mobile application to capture, analyze, and present data insights to patients using a neuro device that treats neuropsychiatric disorders
Design the software and cloud architecture to connect an ophthalmic imaging device to data processing pipelines and deep learning infrastructure
Design a robust data science driven approach to analyze clinical trial participant data with the goal of driving stratification, predicting endpoints, and discovering predictive biomarkers
Identify the most valuable AI/ML use cases for a medical device to improve patient outcomes
Empower telehealth and distributed clinical trial applications with video based heart rate (HR) and variability (HRV) measures
Design and implement a data science platform to support the full life cycle of ML/AI
Migrate existing computer vision pipelines from Vertex AI to Kubeflow
Design and build production architecture for data science models for a medical device
Design and build production architecture for data science models based on time series data from sensors
Natural language processing (NLP) to extract relationships and themes from the evolving COVID-19 scientific literature
Use churn models to guide targeted retention strategies
A better way to assess patients with depression and anxiety for a company bringing new therapeutics to market for neuropsychiatric disorders
Analyze plant genomic data and recommend genetic engineering targets to increase yield and resilience of important, staple food crops using a scalable AI platform
Design and build a realtime gaze tracking application to assess cognitive performance in dementia, concussion, and intoxication patient cohorts
Analyze proteomics data to guide the next phase of drug development of a novel candidate that showed promise in in-vitro and in-vivo studies
Identify therapeutic candidates via multiomics informatics and evaluate top candidates against published literature to prioritize the best targets for drug development
Machine learning to maximize signal-to-noise to differentiate between normal and malignant tissue.
Automatically evaluate which MRI scans can be used for subsequent analysis and modeling
Better prioritize and allocate resources to the most serious claims
Create a strategy to build a data engineering team to support a biotech company's rapid growth.
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