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The Computational Medicine Laboratory (CML) at the University of Houston is currently looking to recruit one highly motivated and creative postdoctoral associate with applied mathematics and/or signal processing background to develop mathematical algorithms for biomedical engineering applications. CML mainly focuses on designing control, optimization, estimation, signal processing, and machine learning algorithms for biomedical and neural engineering applications.
Lecture Date: December 10, 2018
Chapter: Victorian Australia
Chapter Chair: Abd-Krim Seghuane
Topic: Data Fusion Through Matrix and Tensor Factorizations:
Uniqueness, Diversity, and Interpretability
Lecture Date: December 4, 2018
Chapter: South Australia
Chapter Chair: Brian Ng
Topic: Data Fusion Through Matrix and Tensor Factorizations:
On Current Solutions and Challenges
Lecture Date: November 21, 2018
Chapter: Western Australia
Chapter Chair: Sven Nordholm
Topic: Data Fusion Through Matrix and Tensor Factorizations:
On Current Solutions and Challenges
Lecture Date: November 7, 2018
Chapter:Tokyo/Fukuoka/Hiroshima/ Nagoya/<br />Sapporo/Shikoku/ Shin-Etsu Joint Chapter
Chapter Chair: Shoji Makino
Topic: Hyperspectral Unmixing: Insights and Beyond
Lecture Date: November 12, 2018
Chapter: Rochester
Chapter Chair: Raymond Ptucha
Topic: Graph Signal Processing: Distributed Graph Filters
Lecture Date: November 7, 2018
Chapter: Rochester
Chapter Chair: Raymond Ptucha
Topic: Graph Signal Processing: Distributed Graph Filters
Lecture Date: November 2, 2018
Chapter: Philadelphia
Chapter Chair: Michael Mayor
Topic: Statistical Inference through Sparse Sensing