<div dir="ltr"><br clear="all"><div><h1 class="entry-title" style="box-sizing:border-box;margin:0.65rem 0px 0px;line-height:1.3;word-break:break-word">Data Scientist position: Computer vision and other AI techniques in support ocean, atmospheric aerosol, and cloud remote sensing</h1><div class="entry-content" style="box-sizing:border-box;color:rgb(0,0,0);font-family:"Inter var","Helvetica Neue",Helvetica,Arial,sans-serif;font-size:medium"><p style="box-sizing:border-box;font-size:1rem;margin-top:0.5rem"><span style="box-sizing:border-box">The Goddard Earth Sciences Technology and Research II (GESTAR II) consortium at NASA’s Goddard Space Flight Center (GSFC) invites applications for a data scientist position in Physical Science, Computer Science, Engineering, Statistics, Mathematics, or related field. </span></p><p style="box-sizing:border-box;font-size:1rem"> </p><p style="box-sizing:border-box;font-size:1rem"><span style="box-sizing:border-box">The incoming scientist will join the NASA GSFC Ocean Ecology Laboratory </span><a href="https://science.gsfc.nasa.gov/earth/oceanecology/" style="box-sizing:border-box;background-color:rgba(0,0,0,0);padding:1px 2px;color:rgb(0,113,118)"><span style="box-sizing:border-box">(science.gsfc.nasa.gov/earth/oceanecology</span></a><span style="box-sizing:border-box">) to develop novel computer vision and other AI techniques in support of ocean, atmospheric aerosol, and cloud remote sensing. The candidate should be an independent scientist who:</span></p><ul style="box-sizing:border-box;padding-left:1rem;margin-left:0.25rem"><li style="box-sizing:border-box;margin-bottom:0.25rem;padding:0.2rem 0px;font-size:1rem"><span style="box-sizing:border-box">can apply state of the art methods in the analysis and processing of unique remote sensing data, such as those from multi-angle polarimeters,</span></li><li style="box-sizing:border-box;margin-bottom:0.25rem;padding:0.2rem 0px;font-size:1rem"><span style="box-sizing:border-box">is dedicated to our goal of producing scientifically relevant geophysical data products, and</span></li><li style="box-sizing:border-box;margin-bottom:0.25rem;padding:0.2rem 0px;font-size:1rem"><span style="box-sizing:border-box">is able to communicate and interact effectively with non-specialists to implement practical solutions at scale.   </span></li></ul><p style="box-sizing:border-box;font-size:1rem"> </p><p style="box-sizing:border-box;font-size:1rem"><span style="box-sizing:border-box">The position will primarily support two forthcoming NASA missions. The NASA Plankton, Aerosol, Cloud, ocean Ecosystem Mission (PACE, </span><a href="https://pace.gsfc.nasa.gov/" style="box-sizing:border-box;background-color:rgba(0,0,0,0);padding:1px 2px;color:rgb(0,113,118)"><span style="box-sizing:border-box">pace.gsfc.nasa.gov</span></a><span style="box-sizing:border-box">) will be launched in 2024. PACE will have three passive sensors with groundbreaking spectral, polarimetric and multi-angle observing capability. The NASA Atmosphere Observing System Mission (AOS, </span><a href="https://aos.gsfc.nasa.gov/" style="box-sizing:border-box;background-color:rgba(0,0,0,0);padding:1px 2px;color:rgb(0,113,118)"><span style="box-sizing:border-box">aos.gsfc.nasa.gov</span></a><span style="box-sizing:border-box">) will utilize multiple active and passive sensors on several spacecraft launched in the 2028-2030 timeframe for observation of atmospheric aerosols, clouds, convection and precipitation. Both missions will have passive, polarimetrically sensitive, imagers that make multi-angle observations in the UV-SWIR. The corresponding data are very rich, but efficient analysis and processing at a global remote sensing scale is the core challenge the successful applicant will address.  </span></p><p style="box-sizing:border-box;font-size:1rem"><span style="box-sizing:border-box"> </span></p><p style="box-sizing:border-box;font-size:1rem"><span style="box-sizing:border-box;font-weight:bolder">Required Qualifications:</span></p><ul style="box-sizing:border-box;padding-left:1rem;margin-left:0.25rem"><li style="box-sizing:border-box;margin-bottom:0.25rem;padding:0.2rem 0px;font-size:1rem"><span style="box-sizing:border-box">Degree in Physical Science, Computer Science, Engineering, Statistics, Mathematics, or related field and minimum of 4 years of relevant experience, or an equivalent combination of education and experience.</span></li><li style="box-sizing:border-box;margin-bottom:0.25rem;padding:0.2rem 0px;font-size:1rem"><span style="box-sizing:border-box">Experience with scientific programming in C/C++, Fortran, Python, IDL or equivalent.</span></li><li style="box-sizing:border-box;margin-bottom:0.25rem;padding:0.2rem 0px;font-size:1rem"><span style="box-sizing:border-box">Experience applying machine learning methods to solve computer vision and similar problems.</span></li></ul><p style="box-sizing:border-box;font-size:1rem"> </p><p style="box-sizing:border-box;font-size:1rem"><span style="box-sizing:border-box;font-weight:bolder">Desired Experience</span></p><ul style="box-sizing:border-box;padding-left:1rem;margin-left:0.25rem"><li style="box-sizing:border-box;margin-bottom:0.25rem;padding:0.2rem 0px;font-size:1rem"><span style="box-sizing:border-box">Satellite data geolocation and projection.</span></li><li style="box-sizing:border-box;margin-bottom:0.25rem;padding:0.2rem 0px;font-size:1rem"><span style="box-sizing:border-box">Atmosphere, ocean and land surface radiative transfer. Creation of machine learning radiative transfer emulators.  </span></li><li style="box-sizing:border-box;margin-bottom:0.25rem;padding:0.2rem 0px;font-size:1rem"><span style="box-sizing:border-box">Remote sensing of the ocean, atmosphere and land surface.</span></li><li style="box-sizing:border-box;margin-bottom:0.25rem;padding:0.2rem 0px;font-size:1rem"><span style="box-sizing:border-box">Remote sensing with passive multi-angle polarimetric instruments.</span></li><li style="box-sizing:border-box;margin-bottom:0.25rem;padding:0.2rem 0px;font-size:1rem"><span style="box-sizing:border-box">Scientific software development in a high-performance computing environment.</span></li><li style="box-sizing:border-box;margin-bottom:0.25rem;padding:0.2rem 0px;font-size:1rem"><span style="box-sizing:border-box">Application of Bayesian inference techniques.</span></li><li style="box-sizing:border-box;margin-bottom:0.25rem;padding:0.2rem 0px;font-size:1rem"><span style="box-sizing:border-box">Evaluation / validation of satellite observations against reference data sources.</span></li></ul><p style="box-sizing:border-box;font-size:1rem"><span style="box-sizing:border-box">The successful candidate will join the GESTAR II Consortium which supports over 120 researchers based primarily at NASA Goddard Space Flight Center (GSFC). GESTAR II researchers work to create extensive opportunities for breakthroughs in earth and atmospheric science research, carrying out observational, experimental and theoretical research in support of NASA strategic Earth Science mission objectives.</span></p><p style="box-sizing:border-box;font-size:1rem"> </p><p style="box-sizing:border-box;font-size:1rem"><span style="box-sizing:border-box">Goddard’s Earth Science Division is home to about 200 civil servants and over 1200 collaborating researchers and support personnel, dedicated to studying the Earth as an integrated system that includes the atmosphere, oceans, biosphere, cryosphere, and geosphere. The Division operates as a component of the Sciences and Exploration Directorate that collaborate on interdisciplinary research with the Astrophysics Science, Heliophysics Science, and Solar System Exploration Divisions.</span></p><p style="box-sizing:border-box;font-size:1rem"> </p><p style="box-sizing:border-box;font-size:1rem"><span style="box-sizing:border-box">The nominal starting date is </span><span style="box-sizing:border-box">early spring</span><span style="box-sizing:border-box">, but alternate dates are possible depending on availability. </span></p><p style="box-sizing:border-box;font-size:1rem"> </p><p style="box-sizing:border-box;font-size:1rem"><span style="box-sizing:border-box">Candidates should provide a cover letter, CV (including publication list) and a 3-page statement of research interests. Short-listed candidates will be asked to supply three letters of reference at a later date. All materials and inquiries should be sent by email Subject line: Task 175: Researcher Position to: Halley Thompson (</span><a href="mailto:halleyt@umbc.edu" style="box-sizing:border-box;background-color:rgba(0,0,0,0);padding:1px 2px;color:rgb(0,113,118)"><span style="box-sizing:border-box">halleyt@umbc.edu</span></a><span style="box-sizing:border-box">)</span></p><p style="box-sizing:border-box;font-size:1rem"> </p><p style="box-sizing:border-box;font-size:1rem"><span style="box-sizing:border-box">Completed applications received by February 17, 2023, will receive full consideration, however the posting will remain open until the position is filled.</span></p><p style="box-sizing:border-box;font-size:1rem"> </p><p style="box-sizing:border-box;font-size:1rem"><span style="box-sizing:border-box">Salary and benefits are competitive, commensurate with experience and qualifications. The GESTAR II consortium and NASA GSFC are committed to building a diverse research community and encourage applications from women, racial and ethnic minorities, individuals with disabilities and veterans. All GESTAR II institutions are Affirmative Action, Equal Opportunity Employers.</span></p><p style="box-sizing:border-box;font-size:1rem"><span style="box-sizing:border-box">For more information about the proposed research, contact Dr. Kirk Knobelspiesse (</span><a href="mailto:kirk.d.knobelspiesse@nasa.gov" style="box-sizing:border-box;background-color:rgba(0,0,0,0);padding:1px 2px;color:rgb(0,113,118)"><span style="box-sizing:border-box">kirk.d.knobelspiesse@nasa.gov</span></a><span style="box-sizing:border-box">).</span></p></div></div>-- <br><div dir="ltr" class="gmail_signature" data-smartmail="gmail_signature"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div><font size="2"><span style="font-family:arial,sans-serif"><p style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><font color="#222222"><span style="white-space:pre-wrap"><b>Halley Thompson, MPA, PHR</b></span></font></p><p style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><font color="#222222"><span style="white-space:pre-wrap">she/they (<a href="https://www.glsen.org/activity/pronouns-guide-glsen" target="_blank">what's this?</a>)<br></span></font></p><p style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><font color="#222222"><span style="white-space:pre-wrap"></span></font></p><p style="line-height:1.38;margin-top:0pt;margin-bottom:0pt">Program Specialist<br></p><p style="line-height:1.38;margin-top:0pt;margin-bottom:0pt">GESTAR II at MSU</p><p style="line-height:1.38;margin-top:0pt;margin-bottom:0pt">Hiring Specialist</p></span></font><p style="line-height:normal;margin:0in 0in 0pt"><font color="#000000" face="arial, sans-serif">GESTAR II Consortium</font></p><p style="line-height:normal;margin:0in 0in 0pt"><font color="#000000" face="arial, sans-serif"><img width="96" height="93" src="https://ci3.googleusercontent.com/mail-sig/AIorK4wpmfe974n4YScH_v1pR1JVgyc7K44vxoG9_-ZboF8TYCRUMf0umbTEWib29HXWnGvKu8oDeow"><br></font></p><span><p style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><font face="arial, sans-serif" color="#222222"><span style="font-size:14.6667px;white-space:pre-wrap"></span></font></p></span></div></div></div></div></div></div></div>