<div dir="ltr"><div>[Reposting, as position remains unfilled. Please disseminate widely.]<br></div><div><br></div><div>The PLACES lab at Boston University (BU) is offering an NSF-funded position for a <b>postdoctoral researcher or research scientist</b> with a strong skillset in spatiotemporal statistics, machine learning, or causal inference, and an interest in land conservation policy in the United States.</div><div><br></div><div>The successful candidate will contribute to the development of U.S.-wide, parce<font size="2"><span style="font-family:arial,sans-serif">l-level estimates of land value and the cost of long-term conservation (land purchase, easements)*. Findings and products will support policy analyses and decision-making processes of academic, federal, and non-profit stakeholders interested in identifying effective and equitable land use choices under the federal administration's current initiative to protect 30% of the U.S. by 2030. The research is to be funded under NSF's Human-Environment & Geographical Sciences program.</span></font></div><div><font size="2"><span style="font-family:arial,sans-serif"><span></span></span></font></div><div class="gmail_quote"><div dir="ltr"><font size="2"><span style="font-family:arial,sans-serif">
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</span></font><p class="MsoNormal" style="margin:0in"><font size="2"><span style="font-family:arial,sans-serif">The researcher will have the opportunity to work with a unique and fascinating dataset that is scheduled to expire on Sept 30, 2023: geospatial data of 150 million U.S. properties and sales with a wide range of social and environmental characteristics (<a href="http://placeslab.org/dictionary">placeslab.org/dictionary</a>). Research priorities will be defined jointly. Creative extensions are welcome.<br><span></span></span></font></p><font size="2"><span style="font-family:arial,sans-serif">
</span></font><p class="MsoNormal" style="margin:0in"><font size="2"><span style="font-family:arial,sans-serif"><br></span></font></p><p class="MsoNormal" style="margin:0in"><font size="2"><span style="font-family:arial,sans-serif">The ideal candidate will have:<br></span></font></p><ul><li><font size="2"><span style="font-family:arial,sans-serif">A PhD (or similar experience) in economics, statistics, data science, geography, environmental science, or a similar field with a strong quantitative research profile.</span></font></li><li><font size="2"><span style="font-family:arial,sans-serif">Prior experience with geospatial statistics, machine learning, and/or econometrics (in particular causal inference from observational data).</span></font></li><li><font size="2"><span style="font-family:arial,sans-serif">An emerging publication record in peer-reviewed journals.</span></font></li><li><font size="2"><span style="font-family:arial,sans-serif">Interest in understanding land conservation policy in the United States.</span></font></li></ul><font size="2"><span style="font-family:arial,sans-serif"></span></font><font size="2"><span style="font-family:arial,sans-serif"></span></font><p class="MsoNormal" style="margin:0in"><font size="2"><span style="font-family:arial,sans-serif">Knowledge in the following domains will be an asset (but not
expected):<span></span></span></font></p><ul><li>Geospatial packages in Python (geopandas, rasterio, etc.).<font size="2"><span style="font-family:arial,sans-serif"></span></font></li><li><font size="2"><span style="font-family:arial,sans-serif">Parallelized computing (Linux, SunGrid).<span></span></span></font><font size="2"><span style="font-family:arial,sans-serif"><br></span></font></li><li><font size="2"><span style="font-family:arial,sans-serif">Principles of land and easement valuation.<span></span></span></font></li></ul><font size="2"><span style="font-family:arial,sans-serif">
</span></font><p class="MsoNormal" style="margin:0in"><font size="2"><span style="font-family:arial,sans-serif">The position starts as soon as possible, ideally not after Sept 2022. The initial contract duration will be 18 months. Remote work is an option. Continuation of this research with other data is contingent on the success of grants to which the candidate can contribute. BU offers a competitive salary ($62K) and benefits package.<span></span></span></font></p><font size="2"><span style="font-family:arial,sans-serif">
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</span></font><p class="MsoNormal" style="margin:0in"><font size="2"><span style="font-family:arial,sans-serif">Interested applicants should contact Christoph Nolte (<a href="mailto:chrnolte@bu.edu">chrnolte@bu.edu</a>) with their CV, a letter of interest that includes a statement of fit with the position, publications, and contact information of 2-3 reference letter writers. Review of applications will begin on June 1, 2022, and occur on a <b>rolling basis</b> until the position is filled. For updates on the status of this search, visit: <a href="http://placeslab.org/postdoc">placeslab.org/postdoc</a>.<span></span></span></font></p><font size="2"><span style="font-family:arial,sans-serif">
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</span></font><p class="MsoNormal" style="margin:0in"><font size="2"><span style="font-family:arial,sans-serif">BU is an equal opportunity employer and all qualified
applicants will receive consideration for employment without regard to race,
color, religion, sex, national origin, disability status, protected veteran
status, or any other characteristic protected by law.<span></span></span></font></p><font size="2"><span style="font-family:arial,sans-serif">
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</span></font><p class="MsoNormal" style="margin:0in"><font size="2"><span style="font-family:arial,sans-serif">* For more information, visit <a href="http://placeslab.org/fmv_usa" style="color:rgb(5,99,193);text-decoration:underline" target="_blank">placeslab.org/fmv_usa</a> or
consult the following articles:<span></span></span></font></p><font size="2"><span style="font-family:arial,sans-serif">
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</span></font><p class="MsoNormal" style="margin:0in"><font size="2"><span style="font-family:arial,sans-serif">Nolte (2020) High-resolution land value maps reveal
underestimation of conservation cost in the United States. PNAS (<a href="https://www.pnas.org/doi/10.1073/pnas.2012865117" style="color:rgb(5,99,193);text-decoration:underline" target="_blank">link</a>)<span></span></span></font></p><font size="2"><span style="font-family:arial,sans-serif">
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</span></font><p class="MsoNormal" style="margin:0in"><font size="2"><span style="font-family:arial,sans-serif">Nolte et al. (2021) Studying the impacts of environmental amenities
and hazards with nationwide property data: best data practices for interpretable
and reproducible analyses. SSRN (<a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3900806" style="color:rgb(5,99,193);text-decoration:underline" target="_blank">link</a>)</span></font></p><div><br></div><div>-- </div><div dir="ltr" data-smartmail="gmail_signature"><div dir="ltr"><span><span><b>Christoph Nolte</b><br><span><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div>Assistant Professor<br><div>Earth & Environment<br>Boston University</div><div><a href="mailto:chrnolte@bu.edu" target="_blank">chrnolte@bu.edu</a></div><div><a href="http://www.placeslab.org" target="_blank">www.placeslab.org</a><br></div></div></div></div></div></div></div></div></div></div></div></div></span></span></span></div></div></div>
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