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<p class="MsoNormal" style="margin-bottom:4.0pt;text-align:justify"><b><u><span lang="EN-GB" style="color:black">PhD position in understanding of human behaviour during automated driving</span></u><o:p></o:p></b></p>
<p>We are seeking a highly motivated and talented Vision Science and Human Factors PhD Researcher to join an interdisciplinary research project, conducted in collaboration with Queensland University of Technology (QUT) and industry partner Seeing Machines—world
leader in human-machine interaction and an industry leader in artificial intelligence (AI), that enable machines to see, understand and assist the people who are using them.<o:p></o:p></p>
<p>The project aims to advance the understanding of human behaviour during automated driving, with a strong focus on eye, gaze, and head tracking using Seeing Machines’ optimised driver monitoring system technology. The new knowledge is expected to inform novel
strategies that contribute to the safe introduction of Automated Vehicles.<o:p></o:p></p>
<p class="MsoNormal"><b><u>Responsibilities:<o:p></o:p></u></b></p>
<p class="MsoNormal"><o:p> </o:p></p>
<ul style="margin-top:0cm" type="disc">
<li class="MsoListParagraph" style="margin-left:0cm;mso-list:l1 level1 lfo1">Design and develop novel techniques and interfaces for monitoring and assessing driver engagement in L2-L4 driving environments.<o:p></o:p></li><li class="MsoListParagraph" style="margin-left:0cm;mso-list:l1 level1 lfo1">Collaborate with interdisciplinary research teams from QUT and Seeing Machines to integrate findings from other PhD projects into the broader research objectives.<o:p></o:p></li><li class="MsoListParagraph" style="margin-left:0cm;mso-list:l1 level1 lfo1">Work closely with industry partner Seeing Machines to gain insights into driver monitoring systems and leverage their expertise in interface design.<o:p></o:p></li><li class="MsoListParagraph" style="margin-left:0cm;mso-list:l1 level1 lfo1">Conduct empirical studies to evaluate the effectiveness of different HMI designs in sharing attention between drivers and autonomous systems.<o:p></o:p></li><li class="MsoListParagraph" style="margin-left:0cm;mso-list:l1 level1 lfo1">Contribute to the development of guidelines and best practices for designing intuitive and effective HMIs in autonomous vehicles.<o:p></o:p></li><li class="MsoListParagraph" style="margin-left:0cm;mso-list:l1 level1 lfo1">Collaborate with other PhD researchers to support interdisciplinary learning and foster a cohesive research environment.<o:p></o:p></li><li class="MsoListParagraph" style="margin-left:0cm;mso-list:l1 level1 lfo1">Publish research findings in high-impact journals and present at relevant conferences and workshops.<o:p></o:p></li></ul>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal"><b><u>Qualifications and Skills:<o:p></o:p></u></b></p>
<p class="MsoNormal"><o:p> </o:p></p>
<ul style="margin-top:0cm" type="disc">
<li class="MsoListParagraph" style="margin-left:0cm;mso-list:l0 level1 lfo2">A Master's degree (or equivalent) in Human-Computer Interaction, Human Factors, Cognitive Psychology, or a related discipline.<o:p></o:p></li><li class="MsoListParagraph" style="margin-left:0cm;mso-list:l0 level1 lfo2">Strong research background in HCI/HMI, interface design, cognitive psychology, or a relevant field.<o:p></o:p></li><li class="MsoListParagraph" style="margin-left:0cm;mso-list:l0 level1 lfo2">Strong analytical and problem-solving skills, with the ability to translate user insights into actionable design recommendations.<o:p></o:p></li><li class="MsoListParagraph" style="margin-left:0cm;mso-list:l0 level1 lfo2">Excellent communication skills, both written and verbal, for presenting research findings and collaborating with interdisciplinary teams.<o:p></o:p></li><li class="MsoListParagraph" style="margin-left:0cm;mso-list:l0 level1 lfo2">Ability to work independently and as part of a team, managing multiple tasks and priorities effectively.<o:p></o:p></li></ul>
<p>Further details can be found at <o:p></o:p></p>
<p><a href="https://www.qut.edu.au/study/fees-and-scholarships/scholarships/understanding-gaze-behaviour-during-real-world-automated-driving-phd-scholarship">https://www.qut.edu.au/study/fees-and-scholarships/scholarships/understanding-gaze-behaviour-during-real-world-automated-driving-phd-scholarship</a><o:p></o:p></p>
<p>You'll receive a stipend scholarship of AUD $30,000 per annum for a maximum duration of 3.5 years while undertaking a QUT PhD. The duration includes an extension of up to 6 months (PhD) if approved for your candidature. This is the full-time, tax-free rate
which will index annually. The PhD project is linked with industry partner Seeing Machines Pty Ltd, so you may be eligible to apply for a stipend top-up via the
<a href="https://www.education.gov.au/university-research-commercialisation-package/national-industry-phd-program" target="_blank">
National Industry PhD Program</a>.<o:p></o:p></p>
<p>If you're an international student, you will also receive a tuition fee sponsorship for your research degree.<o:p></o:p></p>
<p>As the scholarship recipient, you will have the opportunity to work with a team of leading researchers, to undertake your own innovative research in and across the field.<o:p></o:p></p>
<p>If you have any questions about the position, please get in touch with us directly (Alex Black
<a href="mailto:aa.black@qut.edu.au">aa.black@qut.edu.au</a> or Joanne Wood <a href="mailto:j.wood@qut.edu.au">
j.wood@qut.edu.au</a>).<o:p></o:p></p>
<p><o:p> </o:p></p>
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