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<p class="p1"><span style="font-size:12.0pt">Dear all,<o:p></o:p></span></p>
<p class="p1"><span style="font-size:12.0pt"><o:p> </o:p></span></p>
<p class="p2"><span style="font-size:12.0pt">Prof. Yongli Wager’s Sustainable Water-Environment-Energy Technologies Lab (SWEET lab) at Wayne State University (Michigan) invites applications for a PhD GRA position starting from Winter or Fall of 2023. This position
is full-funded for five years. The candidate is expected to work on a NIEHS-funded project with research interest in real-time monitoring of vapor intrusion (VI) of volatile organic compounds (VOCs). Particularly, we will integrate the Internet of Things (IoT)
sensor network with edge computing (IoTEC), including advanced data collection/processing and a machine learning algorithm for sensor signal pattern recognition under different environmental conditions, for accurate, energy- and cost-efficient VOCs VI monitoring/screening
with varying sensor placements and spatial/temporal intervals. Accuracy and energy- and cost-saving of the IoTEC monitoring will be compared with off-line sampling methods and conventional monitoring approaches at field study sites. Dr. Wager’s research focuses
on water-environment-energy sustainability in an urban environment by using both experimental research and system modeling approach. This project is one of her research focuses, as particularly pertaining to environmental pollution monitoring and remediation.<span class="apple-converted-space"> <o:p></o:p></span></span></p>
<p class="p2"><span style="font-size:12.0pt"><o:p> </o:p></span></p>
<p class="p2"><span style="font-size:12.0pt">Ideal candidates should have earned a Master’s degree or an equivalent degree in environmental engineering, chemical engineering, chemistry, or other related fields. They are expected to have research experience
in environmental pollution monitoring (particularly VOCs), gas sensors, analytical instrument such as GC/LC, and computing techniques (programing, cloud-based data processing, and machine learning). Interested applicants please contact Dr. Yongli Wager (<span class="s2">zhangyl@wayne.edu</span>)
for more details regarding the research project and the application procedure. The information regarding Dr. Wager’s group can be found at
<span class="s2">https://engineering.wayne.edu/profile/ft4970</span>.<span class="apple-converted-space"> </span><o:p></o:p></span></p>
<p class="MsoNormal"><span style="color:black"><o:p> </o:p></span></p>
<p class="MsoNormal"><span style="color:black">Best,<o:p></o:p></span></p>
<p class="MsoNormal"><span style="color:black"><o:p> </o:p></span></p>
<p class="MsoNormal"><span style="color:black">Yaoxian</span></p>
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