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Opportunity at Air Force Research Laboratory (AFRL)

Exploring Elementary MultiSensor Fusion


Information Directorate, RI/Information Exploitation

RO# Location
13.20.91.C0202 Rome, NY 134414514


name email phone


Experiment planning for multi-sensor experiments; this includes design, develop and test distributed seismic sensor system. Also Python programming of multiple Raspberry Pi and interfacing these to seismic sensors. Implementing interfaces to a GPS receiver and logging the pertinent GPS data. Statistical analysis and frequency analysis of the data logs collected. Exploring new and unconventional clustering analysis of signals. This includes UMPA (Uniform Manifold Approximation and Projection) and SNE (Stochastic Neighborhood Embedding).

1. Applying Ricci Flow to Manifold Learning Yangyang Lia, Ruqian Lu1Academy of Mathematics and Systems Science Key Lab of MADIS, Chinese Academy of Sciences, Beijing & University of Chinese Academy of Sciences, Beijing arXiv:1703.10675v1 [cs.LG] 3 Mar 2017

2. Curvature Estimation for Ricci Flow Embedding  Eilza Xu, Richard C. Wilson and Edwin R. Hancock Department of Computer Science, University of York, York, YO105GH, UK. Email:

3. Ricci flow embedding for rectifying non-Euclidean dissimilarity data Weiping Xu, Edwin R. Hancock, Richard C. Wilson Department of Computer Science, The University of York, York YO10 5DD, UK

4. Manifold alignment using discrete surface Ricci flow Zhongxin Liu, Wenmin Wang, Qun Jin  a) School of Electronic and Computer Engineering, Shenzhen Graduate School, Peking University, China b)  Faculty of Human Sciences, Waseda University, Japan

seismic sensors; python programming; statistical signal analysis; machine learning; clustering; manifold approximation


Citizenship:  Open to U.S. citizens
Level:  Open to Postdoctoral and Senior applicants


Base Stipend Travel Allotment Supplementation
$76,542.00 $4,000.00

$3,000 Supplement for Doctorates in Engineering & Computer Science

Experience Supplement:
Postdoctoral and Senior Associates will receive an appropriately higher stipend based on the number of years of experience past their PhD.

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