Dear Colleagues, Our postdoc opportunity might be of interest to you or your team members. The start date is very flexible, and the candidate does not need to check all these boxes, since they will be part of an interdisciplinary team. The bullet points indicate our wish list. Creating software infrastructure for interactive labeling and deep learning to facilitate earth data fusion is central to this position, and we anticipate user studies with expert geoscientists in the future. Regards, Morteza Morteza Karimzadeh, PhD Assistant Professor Department of Geography Affiliate Assistant Professor, Computer Science, Information Science University of Colorado Boulder Traditional Territories of the Arapaho, Cheyenne and Ute Nations 303-492-3252 karimzadeh@colorado.edu<mailto:karimzadeh@colorado.edu> Transdisciplinary Postdoctoral Research Associate Position in Spatial Data Science and Geoscience University of Colorado Boulder, Boulder, CO Starting date (very flexible): 1/7/2021 Application review begins December 7, 2020 on a rolling basis until the position is filled. We invite applications for a postdoctoral research associate position at the Department of Geography, University of Colorado Boulder (CU Boulder), with a flexible starting date of 1/7/2021 and possibility for remote work, although the ability to work on the CU Boulder campus in the long term is desirable. The initial offer is for 12 months, with potential for renewal contingent upon favorable progress. The postdoctoral scholar will primarily work on a recently funded NSF EarthCube project (Data Capabilities: Enabling Analysis of Heterogeneous, Multi-source Cryospheric Data, Award# 2026962) under the supervision of principal investigator, Dr. Morteza Karimzadeh. The project is focused on creating software systems and cyber-infrastructure for harmonizing heterogeneous big data products (including satellite imagery and in situ observations) in a cloud environment for various downstream tasks. The technologies developed are expected to be extendable to a variety of applications, but for this project, the focus will be on classification and mapping of sea ice. Sea ice is an important component of the climate system and a key indicator of climate change. Sea ice is spatiotemporally dynamic, exhibiting a variety of evolving ice types that need classification for scientific analysis or operational planning. The mapping of sea ice at high spatial and temporal resolutions remains a scientific challenge. With the increasing availability of high-resolution remote sensing products such as SAR and lidar, there is a renewed desire for tackling this challenge. However, bridging data science and geoscience is key in successfully harnessing these large heterogeneous data for sea ice mapping. The postdoctoral position will be homed in the Geography Department at CU Boulder and will actively collaborate with the co-PIs, scientists and students in the National Snow and Ice Data Center (NSIDC) and CU Denver’s Department of Computer Science. The postdoc duties will include: * Design and implement software and computational modules in collaboration with the team’s sea ice scientists, remote sensing experts, and spatial data scientists. * Draft and lead scholarly publications and reports. * Assist the PI with leading research activities within the group and project management. * Assist the PI with user evaluations and stakeholder engagement at NSIDC, NOAA, NCAR, the U.S. National Ice Center (NIC) and the Canadian Ice Service (CIS). * Assist in supervising graduate and undergraduate students in the team. * Assist in drafting successful research grant proposals. * Interface with other research groups at and beyond the NSF EarthCube community and the University of Colorado. * Work with research assistants to prepare training and outreach material, including easy-to-use Jupyter notebooks for product adoption. Given the transdisciplinary nature of this postdoctoral position, we expect that the candidate has foundation in either one or both spatial data science and/or geosciences, with the position strengthening the postdoc’s expertise in both disciplines. The qualified candidate will possess a majority of the following, with interest in developing the rest: * A Ph.D. in geography, geoscience, computer science, information science, statistics, or a cognate field is mandatory. * Research background and expertise in applied machine learning and particularly, deep learning. * Background and experience working with, spatial data, geographic information systems and earth observations. * Familiarity with passive and active microwave imagery, airborne and spaceborne lidar altimetry is desirable (examples include SAR imagery from Sentinel-1, lidar altimetry data from Operation IceBridge, ICESat and ICESat-2, and radar altimetry data from CryoSat-2). * Programming skills in Python, Scikit-learn and deep learning libraries (TensorFlow, or Keras or PyTorch). Working ability with R and its spatial packages is a plus. * Interest or background in visual analytics for interactive machine learning is desirable. * Experience working with cloud storage and compute instances is desirable. * Experience in working with the output of climate models is desirable. * Front-end development and visualization skills using D3.js, leaflet.js and the React framework is desirable. * Excellent oral and written communication skills. Both beginning and senior postdoctoral candidates are encouraged to apply. To apply, please upload your CV, a research statement (no more than one page) and the contact information of references to the application portal: https://jobs.colorado.edu/jobs/JobDetail/Postdoctoral-Associate/27487 Please direct your questions to Dr. Morteza Karimzadeh (karimzadeh@colorado.edu<mailto:karimzadeh@colorado.edu>). Applications will be reviewed on a rolling basis starting December 7, 2020 until the position is filled.