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<div class="WordSection1">
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal" align="center" style="text-align:center;background:#FFFDFD">
<b><span style="font-size:11.0pt;font-family:YaleNew;font-variant:small-caps;color:#373737">COMPUTATIONAL SCIENTIST, YALE CENTER FOR NATURAL CARBON CAPTURE<o:p></o:p></span></b></p>
<p class="MsoNormal" align="center" style="text-align:center;background:#FFFDFD">
<b><span style="font-size:11.0pt;font-family:YaleNew;font-variant:small-caps;color:#373737"><o:p> </o:p></span></b></p>
<p class="MsoNormal"><span style="font-size:11.0pt;font-family:YaleNew;color:#373737">The
</span><a href="https://naturalcarboncapture.yale.edu/"><span style="font-size:11.0pt;font-family:YaleNew;color:#0563C1">Yale Center for Natural Carbon Capture</span></a><span style="font-size:11.0pt;font-family:YaleNew;color:#373737"> (YCNCC) at Yale University
is seeking highly qualified candidates who are passionate about mitigating climate change to manage and direct the data and scientific computing needs across the YCNCC. The successful applicant will collaborate with an interdisciplinary team of climate scientists,
physicists, chemists, oceanographers, geochemists, and ecologists to advance the research and deployment of climate change solutions developed at the YCNCC.
</span><span style="font-size:11.0pt;font-family:YaleNew"><o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:11.0pt;font-family:YaleNew"><o:p> </o:p></span></p>
<p class="MsoNormal"><span style="font-size:11.0pt;font-family:YaleNew">As an Affirmative Action/Equal Opportunity employer, Yale University values diversity among its students, staff, and faculty and strongly welcomes applications from women, persons with
disabilities, protected veterans, LGBTQ community members, and persons from racial/ethnic groups historically underrepresented in earth and environmental sciences.<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:11.0pt;font-family:YaleNew"><o:p> </o:p></span></p>
<p class="MsoNormal"><u><span style="font-size:11.0pt;font-family:YaleNew">All applications should be submitted through Interfolio at
</span></u><a href="http://apply.interfolio.com/136985"><span style="font-size:11.0pt;font-family:YaleNew;color:#1155CC">http://apply.interfolio.com/136985</span></a><u><span style="font-size:11.0pt;font-family:YaleNew">. Review of applications will begin on
January 22, 2024, and continue until a suitable candidate is identified.</span></u><u><span style="font-size:11.0pt;font-family:YaleNew"><o:p></o:p></span></u></p>
<p class="MsoNormal" style="margin-top:14.0pt;background:#FFFDFD"><b><span style="font-size:11.0pt;font-family:YaleNew;color:#373737">Key responsibilities</span></b><span style="font-size:11.0pt;font-family:YaleNew;color:#373737"><o:p></o:p></span></p>
<ul style="margin-top:0in" type="disc">
<li class="MsoNormal" style="color:#373737;mso-list:l1 level1 lfo1;background:#FFFDFD">
<span style="font-size:11.0pt;font-family:YaleNew">Support YCNCC researchers on their data and scientific computing needs<o:p></o:p></span></li><li class="MsoNormal" style="color:#373737;mso-list:l1 level1 lfo1;background:#FFFDFD">
<span style="font-size:11.0pt;font-family:YaleNew">Develop and implement a five-year strategy for YCNCC’s scientific computing effort<o:p></o:p></span></li><li class="MsoNormal" style="color:#373737;mso-list:l1 level1 lfo1;background:#FFFDFD">
<span style="font-size:11.0pt;font-family:YaleNew">Analyze large datasets from earth-system models, ocean models, satellite observations, remote sensing, and field experiments using statistical and machine learning tools<o:p></o:p></span></li><li class="MsoNormal" style="color:#373737;mso-list:l1 level1 lfo1;background:#FFFDFD">
<span style="font-size:11.0pt;font-family:YaleNew">Develop decision support tools for climate change solutions based on YCNCC research<o:p></o:p></span></li><li class="MsoNormal" style="color:#373737;mso-list:l1 level1 lfo1;background:#FFFDFD">
<span style="font-size:11.0pt;font-family:YaleNew">Work with YCNCC researchers on proposal development, submission, and execution<o:p></o:p></span></li><li class="MsoNormal" style="color:#373737;margin-bottom:14.0pt;mso-list:l1 level1 lfo1;background:#FFFDFD">
<span style="font-size:11.0pt;font-family:YaleNew">Co-author research findings with YCNCC researchers in leading journals<o:p></o:p></span></li></ul>
<p class="MsoNormal" style="margin-top:14.0pt;background:#FFFDFD"><b><span style="font-size:11.0pt;font-family:YaleNew;color:#373737">Requirements</span></b><span style="font-size:11.0pt;font-family:YaleNew;color:#373737"><o:p></o:p></span></p>
<ul style="margin-top:0in" type="disc">
<li class="MsoNormal" style="color:#373737;mso-list:l0 level1 lfo2;background:#FFFDFD">
<span style="font-size:11.0pt;font-family:YaleNew">PhD in computer science, data science, machine learning, artificial intelligence, physical oceanography, climate science, or related fields<o:p></o:p></span></li><li class="MsoNormal" style="color:#373737;mso-list:l0 level1 lfo2;background:#FFFDFD">
<span style="font-size:11.0pt;font-family:YaleNew">Extensive experience with data science and high-performance computing<o:p></o:p></span></li><li class="MsoNormal" style="color:#373737;mso-list:l0 level1 lfo2;background:#FFFDFD">
<span style="font-size:11.0pt;font-family:YaleNew">Excellent writing and oral communication skills<o:p></o:p></span></li><li class="MsoNormal" style="color:#373737;mso-list:l0 level1 lfo2;background:#FFFDFD">
<span style="font-size:11.0pt;font-family:YaleNew">Ability to, and experience with, working collaboratively in interdisciplinary teams<o:p></o:p></span></li><li class="MsoNormal" style="color:#373737;mso-list:l0 level1 lfo2;background:#FFFDFD">
<span style="font-size:11.0pt;font-family:YaleNew">Ability and willingness to quickly learn new skills<o:p></o:p></span></li><li class="MsoNormal" style="color:#373737;margin-bottom:14.0pt;mso-list:l0 level1 lfo2;background:#FFFDFD">
<span style="font-size:11.0pt;font-family:YaleNew">Record of publishing high-impact journal papers<o:p></o:p></span></li></ul>
<p class="MsoNormal" style="margin-top:14.0pt;background:#FFFDFD"><b><span style="font-size:11.0pt;font-family:YaleNew;color:#373737">Preferred Qualifications<o:p></o:p></span></b></p>
<p class="MsoNormal" style="background:#FFFDFD"><i><span style="font-size:10.0pt;font-family:YaleNew;color:#373737">Note: We encourage applications from candidates who meet one or more of these qualifications. We do not expect that any single candidate will
possess all listed qualifications.<o:p></o:p></span></i></p>
<ul style="margin-top:0in" type="disc">
<li class="MsoNormal" style="color:#373737;mso-list:l2 level1 lfo3;background:#FFFDFD">
<span style="font-size:11.0pt;font-family:YaleNew">Experience with large earth-system datasets (ECCO, GLODAP, PRISM, SSURGO, etc.)<o:p></o:p></span></li><li class="MsoNormal" style="color:#1D1D1D;mso-list:l2 level1 lfo3"><span style="font-size:11.0pt;font-family:YaleNew">Experience with biogeochemical modeling (DayCent, DNDC)
<o:p></o:p></span></li><li class="MsoNormal" style="color:#1D1D1D;mso-list:l2 level1 lfo3"><span style="font-size:11.0pt;font-family:YaleNew;color:black">Experience with geospatial analysis and environmental remote sensing datasets</span><span style="font-size:11.0pt;font-family:YaleNew"><o:p></o:p></span></li><li class="MsoNormal" style="color:#373737;mso-list:l2 level1 lfo3;background:#FFFDFD">
<span style="font-size:11.0pt;font-family:YaleNew">Programming experience in or ability to learn Fortran / C<o:p></o:p></span></li><li class="MsoNormal" style="color:#373737;mso-list:l2 level1 lfo3;background:#FFFDFD">
<span style="font-size:11.0pt;font-family:YaleNew">Background in ocean, climate, and/or earth-system modeling. Experience with common community models (POP, MITgcm, CESM, etc.)<o:p></o:p></span></li><li class="MsoNormal" style="color:#373737;mso-list:l2 level1 lfo3;background:#FFFDFD">
<span style="font-size:11.0pt;font-family:YaleNew">Knowledge of Physics-informed NN frameworks such as SimGAN or NVIDIA’s Modulus<o:p></o:p></span></li><li class="MsoNormal" style="color:#373737;mso-list:l2 level1 lfo3;background:#FFFDFD">
<span style="font-size:11.0pt;font-family:YaleNew">Proficiency in machine learning frameworks (TensorFlow, PyTorch, sklearn, etc.) and languages (Python, C)<o:p></o:p></span></li><li class="MsoNormal" style="color:#373737;mso-list:l2 level1 lfo3;background:#FFFDFD">
<span style="font-size:11.0pt;font-family:YaleNew">Experience applying deep learning and other AI methods to emulate complex model parameterizations<o:p></o:p></span></li><li class="MsoNormal" style="color:#373737;mso-list:l2 level1 lfo3;background:#FFFDFD">
<span style="font-size:11.0pt;font-family:YaleNew">Knowledge of deep learning and neural networks, generative adversarial networks, time series predictive methods such as LSTMs, Bayesian machine learning methods, and statistical learning<o:p></o:p></span></li><li class="MsoNormal" style="color:#373737;mso-list:l2 level1 lfo3;background:#FFFDFD">
<span style="font-size:11.0pt;font-family:YaleNew">Experience with or knowledge of operations research and optimization methods (e.g., convex optimization, nonlinear methods, integer programming, etc.) and associated tools such as Gurobi or Python packages
like “or-tools”<o:p></o:p></span></li><li class="MsoNormal" style="color:#373737;mso-list:l2 level1 lfo3;background:#FFFDFD">
<span style="font-size:11.0pt;font-family:YaleNew">Experience with Bayesian emulation and hierarchical models<o:p></o:p></span></li><li class="MsoNormal" style="color:#373737;mso-list:l2 level1 lfo3;background:#FFFDFD">
<span style="font-size:11.0pt;font-family:YaleNew">Experience with uncertainty quantification and bootstrapping or Markov Chain Monte Carlo (MCMC) methods<o:p></o:p></span></li><li class="MsoNormal" style="color:#373737;margin-bottom:14.0pt;mso-list:l2 level1 lfo3;background:#FFFDFD">
<span style="font-size:11.0pt;font-family:YaleNew">Experience with climate model emulators<o:p></o:p></span></li></ul>
<p class="MsoNormal"><o:p> </o:p></p>
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