Brown University, Division of Applied Mathematics

Position ID: Brown-NASA [#17404]
Position Title: Postdoctoral Research Assistant
Position Type: Postdoctoral
Position Location: Providence, Rhode Island 02912, United States [map]
Subject Areas: statistics, machine learning, computer science, data science, or applied mathematics
Application Deadline: 2021/04/15 11:59PMhelp popup finished (2021/03/03, finished 2021/04/15)
Position Description:   URMs apply  

*** this position has been closed and new applications are no longer being accepted. ***

The Division of Applied Mathematics at Brown University is accepting applications for a postdoctoral research associate in statistics, machine learning, computer science, data science, or applied mathematics. The successful applicant will join a NASA-funded effort to generate new methods for data generation and prediction using spaceborne lidar data. The data are being collected by the Global Ecosystem Dynamics Investigation (GEDI), a multibeam waveform lidar sensor currently in orbit on the International Space Station. The successful applicant will advance NASA capabilities with respect to three issues:

(1) developing a generative waveform model that is representative of sensor noise and other measurement artifacts using a large training data set of coincident airborne and spaceborne lidar data;

(2) development of statistical machine learning models to predict aboveground carbon density using spaceborne lidar in forests and woodlands worldwide, and

(3) improvement of predictive models using semi-supervised learning applied to billions of waveform height measurements from GEDI lidar.

The successful applicant will work directly under the supervision of Dr. Matthew Harrison (Applied Math) and Dr. James Kellner (Institute at Brown for Environment and Society and GEDI co-Investigator). The successful applicant should have a PhD in applied mathematics, biology, computer science, data science, geodesy, geophysics, engineering, machine learning, remote sensing, statistics, or a closely related field. Experience with large datasets is essential. Excellent written and oral communication skills are essential as indicated by a record of peer-reviewed publication, oral presentation, or other means. A strong background in quantitative methods and statistical inference is necessary to succeed in this position. Preference will be given to applicants with exposure to machine learning using large data sets. Applicants with experience using remote sensing, geographic information systems, or other spatial data are desirable but not essential. The successful applicant will be a member of the Division of Applied Mathematics and the Institute at Brown for Environment and Society. The successful applicant will interact with the NASA GEDI Science Team, and with collaborators at the University of Maryland College Park and NASA Goddard Space Flight Center. The initial appointment will be for one year, subject to renewal upon satisfactory performance and funding availability.

All candidates should submit a cover letter, curriculum vitae, and names and contact information for three references. Please apply via mathjobs: www.mathjobs.org/jobs/list/17404.

Applications will be reviewed immediately, and the position will remain open until filled.

Application inquiries should be directed to Matthew_Harrison@brown.edu.

Brown University is committed to fostering a diverse and inclusive academic global community; as an EEO/AA employer, Brown considers applicants for employment without regard to, and does not discriminate on the basis of, gender, race, protected veteran status, disability, or any other legally protected status.


Application Materials Required:
Submit the following items online at this website to complete your application:
And anything else requested in the position description.

Further Info:
https://www.mathjobs.org/jobs/list/17404
401-863-1834
 
Professor Matthew Harrison
Division of Applied Mathematics
Brown University
Box F
Providence, RI 02912

© 2021 MathJobs.Org, American Mathematical Society. All Rights Reserved.