-
of chemical, systems, and synthetic biology, and/or the metabolism of human diseases. Areas of particular interest include leveraging artificial intelligence and deep learning models to understand complex
-
, procedural planning, and outcomes in aortic disease. The ideal candidate will combine deep technical expertise in AI delivery (computer vision, machine learning, multimodal data) with demonstrated experience
-
modeling of post-tuberculosis lung disease risk using approaches including generalized linear models and deep learning. Performs other job-related duties as assigned. Minimum Qualifications MD or Ph.D. in
-
using deep learning, computational chemistry, medicinal chemistry, chemical biology, and molecular cell biology to develop novel therapeutics to tackle complex diseases such as cancers. Postdoctoral
-
and test statistical, optimization, and machine learning models, including regression, classification, clustering, natural language processing, deep learning, and/or statistical modeling using surgical
-
curiosity, a deep appreciation for architectural craft, exceptional collaborative skills, a very strong work ethic and a proactive approach to maintaining a safe, organized, and cutting-edge laboratory
-
, Computer Science or a related quantitative field. Strong background in machine learning and statistical modeling, with experience in deep learning frameworks (e.g., PyTorch or TensorFlow). Familiarity with modern