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<p class="MsoNormal" style="background:white;vertical-align:baseline"><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:#333333">A post-doctoral position is available in the Cancer Data Science Lab in computational structural biology to study
the structure and function of cell surface proteins and engineer optimized chimeric antigen receptor constructs, <em><span style="font-family:"Arial",sans-serif;border:none windowtext 1.0pt;padding:0in">integrating structural, biophysical and biological constraints</span></em>.
It is a key position in an interdisciplinary project bridging structural biology (cryoEM, NMR, Xray), computational biology, cell biology and clinical trials.<o:p></o:p></span></p>
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<p class="MsoNormal" style="background:white;vertical-align:baseline"><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:#333333">Chimeric Antigen Receptors (CAR) are the backbone of CAR-T cell therapies (<a href="https://urldefense.proofpoint.com/v2/url?u=https-3A__www.cancer.gov_about-2Dcancer_treatment_research_car-2Dt-2Dcells&d=DwMGaQ&c=-35OiAkTchMrZOngvJPOeA&r=L7-zyQ-04fFCMRqzLIOnx7H0exGZHwIQe_wMPuY600I&m=TcOOCuASaHFELSUeUxIH1LzCoycN4-49jw-eceJiZJgr_HiRiKgtSp8NF4CSA5_Q&s=6UTqhm1wgHFaOl28kr2Wzi5hcLvIgg-nzt0NORn6efk&e="><span style="color:#357DB4;border:none windowtext 1.0pt;padding:0in">https://www.cancer.gov/about-cancer/treatment/research/car-t-cells</span></a>).
They are the focus of over 700 clinical studies being conducted worldwide.<o:p></o:p></span></p>
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<p class="MsoNormal" style="background:white;vertical-align:baseline"><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:#333333">Many teams throughout the world are focusing on the optimization of CAR-Ts for the treatment of patients with relapsed/refactory
cancers but the vast majority of studies are performed by an empirical trial and error approach. This project brings together expertise in CAR-T cell biology, structural biology, computational structural modeling and machine learning to develop a rational
design approach.<o:p></o:p></span></p>
<p class="MsoNormal" style="background:white;vertical-align:baseline"><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:#333333"> <o:p></o:p></span></p>
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<span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:#595959">Qualifications:<o:p></o:p></span></h3>
<p class="MsoNormal" style="background:white;vertical-align:baseline"><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:#333333">The candidates should hold a Ph.D. degree, have at least one first author publication and have a strong knowledge
of protein structure. Experience in protein modeling, molecular dynamics simulations (Amber, NAMD, CHARMM, Gromacs etc.), and biophysics methods is needed. Artificial Intelligence (Machine learning) experience and/or software development experience are a
plus but not required.<o:p></o:p></span></p>
<p class="MsoNormal" style="background:white;vertical-align:baseline"><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:#333333"> <o:p></o:p></span></p>
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<span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:#595959">To Apply:<o:p></o:p></span></h3>
<p class="MsoNormal" style="background:white;vertical-align:baseline"><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:#333333">Interested individuals should send a cover letter outlining research interests and long-term goals, CV and the
names of three references to:<o:p></o:p></span></p>
<p class="MsoNormal" style="background:white;vertical-align:baseline"><strong><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:#333333;border:none windowtext 1.0pt;padding:0in">Philippe Youkharibache, Ph.D.</span></strong><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:#333333"> <a href="mailto:philippe.youkharibache@nih.gov"><span style="color:#357DB4;border:none windowtext 1.0pt;padding:0in">philippe.youkharibache@nih.gov</span></a><o:p></o:p></span></p>
<p class="MsoNormal" style="background:white;vertical-align:baseline"><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:#333333"> <o:p></o:p></span></p>
<p class="MsoNormal" style="background:white;vertical-align:baseline"><em><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:#333333;border:none windowtext 1.0pt;padding:0in">The NIH is dedicated to building a diverse community in its training
and employment programs and encourages the application and nomination of qualified women, minorities, and individuals with disabilities</span></em><span style="font-size:11.0pt;font-family:"Arial",sans-serif;color:#333333">. <em><span style="font-family:"Arial",sans-serif;border:none windowtext 1.0pt;padding:0in">DHHS
and NIH are Equal Opportunity Employers.</span></em><o:p></o:p></span></p>
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