-
Education and Experience: Appropriate PhD in a related field. Preferred Qualifications: Experience with machine learning and deep neural network techniques. Experience with wearable and sensors placed in
-
application of advanced deep learning models, with an emphasis on techniques such as knowledge distillation. The candidate will engage in research involving time-series analysis, including modeling, forecasting
-
fundamental research Developing compound flooding model with coverage of coastal land, estuaries, and deep ocean. Conducting fundamental research by integrating long-term observational data and high-resolution
-
machine learning, deep learning, data visualization, and applied analytics for multi-modal datasets. Technical proficiency with Python, R, SQL, SPSS, Tableau. Architectural and design software expertise
-
upon future funding. Qualifications Required Education and Experience Appropriate PhD in a related field. Preferred Qualifications Experience with machine learning and deep neural network techniques
-
Measure Theory : Leveraging foundational mathematical frameworks to design robust modeling approaches. 2) Deep Learning : Exploring cutting-edge techniques such as multimodal data integration, diffusion
-
organization skills. Experienced in workflow design and technical documentation. PREFERRED QUALIFICATIONS Experience developing AI methods for environmental data sets including working with deep learning