<div dir="ltr"><p class="MsoNormal" align="center" style="margin:12pt 0cm;text-align:center;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;line-height:115%;font-size:11pt;font-family:Arial,sans-serif"><b><i><span lang="EN-US" style="font-size:12pt;line-height:115%;color:black">Prognostics and Health Management solutions
for</span></i></b><b><i><span lang="EN-US" style="font-size:12pt;line-height:115%"></span></i></b></p>

<p class="MsoNormal" align="center" style="margin:12pt 0cm;text-align:center;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;line-height:115%;font-size:11pt;font-family:Arial,sans-serif"><b><i><span lang="EN-US" style="font-size:12pt;line-height:115%;color:black">Reliable Autonomous Systems</span></i></b><b><i><span lang="EN-US" style="font-size:12pt;line-height:115%"></span></i></b></p>

<p class="MsoNormal" style="margin:12pt 0cm 0cm;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;line-height:115%;font-size:11pt;font-family:Arial,sans-serif"><i><u><span lang="EN-US" style="font-size:12pt;line-height:115%">Description</span></u></i></p>

<p class="MsoNormal" style="margin:12pt 0cm 0cm;text-align:justify;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;line-height:115%;font-size:11pt;font-family:Arial,sans-serif"><span lang="EN-US" style="font-size:10pt;line-height:115%;color:rgb(51,51,51)">The revolution in robotics and autonomous systems (RAS) is unstoppable.
The advance of autonomous system applications, such as autonomous transport [1,
2] and autonomous inspections [3], generate multiple benefits for the industry
and society, including the improved driving security in autonomous transport,
and improved reliability of critical and remote infrastructure through
specialized robots and drones.</span></p>

<p class="MsoNormal" style="margin:12pt 0cm 0cm;text-align:justify;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;line-height:115%;font-size:11pt;font-family:Arial,sans-serif"><span lang="EN-US" style="font-size:10pt;line-height:115%;color:rgb(51,51,51)">However, the reliability assurance of RAS is a complex challenge, as it
requires incorporating advanced intelligence that should evolve according to
run-time operation [4]. The challenging yet exciting, operation context of RAS,
hampers the reliability assurance of RAS, which decelerates the acceptance and
everyday use of RAS.</span></p>

<p class="MsoNormal" style="margin:12pt 0cm 0cm;text-align:justify;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;line-height:115%;font-size:11pt;font-family:Arial,sans-serif"><span lang="EN-US" style="font-size:10pt;line-height:115%;color:rgb(51,51,51)">Different technological solutions have emerged to improve the design and
reliability of RAS [5]. Most of the technological configurations include a
combination of mechanical and electrical components, along with onboard
software intelligence to adopt decisions without direct human intervention. In
this context, using the ever-increasing prognostics and health management
solutions, it is possible to develop a prognostics modelling approach for RAS
health monitoring using reliability, machine learning, uncertainty modelling
and optimization methods [6].</span></p>

<p class="MsoNormal" style="margin:12pt 0cm 0cm;text-align:justify;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;line-height:115%;font-size:11pt;font-family:Arial,sans-serif"><span lang="EN-US" style="font-size:10pt;line-height:115%;color:rgb(51,51,51)">The project’s objective is to develop novel prognostics methods for RAS,
which can accurately inform about the model’s confidence in </span><span lang="EN-US" style="font-size:10pt;line-height:115%">the decisions</span><span lang="EN-US" style="font-size:10pt;line-height:115%;color:red"> </span><span lang="EN-US" style="font-size:10pt;line-height:115%;color:rgb(51,51,51)">in
real-time and the way to mitigate the existing problem via optimization
methods, and always, provide a worst-case estimate on its predictions by using
a proper modelling and update of the different sources of uncertainty. In
particular, the work will focus on the integration of uncertainties to make
prognostic predictions robust, using concepts such as adversarial learning,
combined with statistical learning and artificial intelligence methods.<span style="background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"></span></span></p>

<p class="MsoNormal" style="margin:12pt 0cm 0cm;text-align:justify;line-height:115%;font-size:11pt;font-family:Arial,sans-serif"><span lang="EN-US" style="font-size:10pt;line-height:115%;color:rgb(51,51,51);background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial">The models developed in this
project will be validated with the data collected from industry partners that
work with autonomous robots focusing on (i) autonomous remote inspections for
renewable energy and (ii) automotive industry.</span></p>

<p class="MsoNormal" style="margin:12pt 0cm 0cm;text-align:justify;line-height:115%;font-size:11pt;font-family:Arial,sans-serif"><span lang="EN-US" style="font-size:10pt;line-height:115%;color:rgb(51,51,51);background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial">The project will be developed
in</span><a href="https://www.mondragon.edu/en/home"><span style="font-size:10pt;line-height:115%;color:rgb(51,51,51);background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;text-decoration-line:none"> </span></a><span lang="EN-US" style="font-size:10pt;line-height:115%;color:rgb(51,51,51);background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial">Mondragon Unibertsitatea
within the Electronics and Computer Science Department, in collaboration
between the Data Analytics and Signal Processing and Communications groups.
Throughout the thesis, the student will engage continuously with industry and
stays at different universities and/or research centers will be pursued.</span></p>

<p class="MsoNormal" style="margin:12pt 0cm 0cm;text-align:justify;line-height:115%;font-size:11pt;font-family:Arial,sans-serif"><span lang="EN-US" style="font-size:10pt;line-height:115%;color:rgb(51,51,51);background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial">Interested applicants, send
your CV and a short motivation letter to: <a href="mailto:jiaizpurua@mondragon.edu">jiaizpurua@mondragon.edu</a> and <a href="mailto:ezugasti@mondragon.edu">ezugasti@mondragon.edu</a></span></p>

<p class="MsoNormal" style="margin:12pt 0cm 0cm;text-align:justify;line-height:115%;font-size:11pt;font-family:Arial,sans-serif"><span lang="EN-US" style="font-size:10pt;line-height:115%;color:rgb(51,51,51);background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial">Application deadline. Review
of applications will begin July 1st and continue until the position is filled.</span></p>

<p class="MsoNormal" style="margin:12pt 0cm 0cm;text-align:justify;line-height:115%;font-size:11pt;font-family:Arial,sans-serif"><span lang="EN-US" style="font-size:10pt;line-height:115%;color:rgb(51,51,51);background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"> </span></p>

<p class="MsoNormal" style="margin:12pt 0cm 0cm;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;line-height:115%;font-size:11pt;font-family:Arial,sans-serif"><i><u><span lang="EN-US" style="font-size:12pt;line-height:115%">Requirements</span></u></i><b><span lang="EN-US" style="font-size:12pt;line-height:115%"></span></b></p>

<p class="gmail-MsoListParagraphCxSpFirst" style="margin:12pt 0cm 0.0001pt 18pt;text-align:justify;line-height:115%;font-size:11pt;font-family:Arial,sans-serif"></p><ul><li><span lang="EN-US" style="font-size:10pt;line-height:115%;color:rgb(51,51,51);background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial">M.Sc. degree in
telecommunications, electronics, computer science, mathematics, embedded
systems or a related area.</span></li><li><span lang="EN-US" style="font-size:10pt;line-height:115%;color:rgb(51,51,51);background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial">Programming skills: Matlab,
Python, R, or C++ (samples from prior projects or a GitHub</span><span lang="EN-US" style="font-size:7pt;line-height:115%;font-family:"Times New Roman",serif;color:rgb(51,51,51)">         </span><span lang="EN-US" style="font-size:10pt;line-height:115%;color:rgb(51,51,51);background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial">repository are preferred)</span></li><li><span lang="EN-US" style="font-size:10pt;line-height:115%;color:rgb(51,51,51);background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial">Statistics/mathematics, data
science/AI/ML</span></li><li><span lang="EN-US" style="font-size:10pt;line-height:115%;color:rgb(51,51,51);background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial">Knowledge/experience with
autonomous systems is a plus.</span></li><li><span lang="EN-US" style="font-size:10pt;line-height:115%;color:rgb(51,51,51);background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial">Knowledge/experience with
reliability and/or diagnostics/health management methods is a plus.</span></li><li><span lang="EN-US" style="font-size:10pt;line-height:115%;color:rgb(51,51,51);background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial">Experience with artificial
intelligence / optimization methods is a plus.</span></li></ul><p></p>











<p class="MsoNormal" style="margin:12pt 0cm 0cm;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;line-height:115%;font-size:11pt;font-family:Arial,sans-serif"><b>References</b></p>

<p class="MsoNormal" style="margin:12pt 0cm 0cm;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;line-height:115%;font-size:11pt;font-family:Arial,sans-serif"><b> </b></p>

<p class="MsoNormal" style="text-align:justify;margin:0cm;line-height:115%;font-size:11pt;font-family:Arial,sans-serif"><span style="font-size:10pt;line-height:115%;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial">[1] Feng,
S., Yan, X., Sun, H. et al. </span><span lang="EN-US" style="font-size:10pt;line-height:115%;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial">Intelligent driving intelligence test for autonomous vehicles with
naturalistic and adversarial environment. <i>Nature
Communications</i> 12, 748 (2021).</span><a href="https://doi.org/10.1038/s41467-021-21007-8"><span style="font-size:10pt;line-height:115%;color:rgb(34,34,34);background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;text-decoration-line:none"> </span></a><a href="https://doi.org/10.1038/s41467-021-21007-8"><span lang="EN-US" style="font-size:10pt;line-height:115%;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial">https://doi.org/10.1038/s41467-021-21007-8</span></a><u><span lang="EN-US" style="font-size:10pt;line-height:115%;color:rgb(17,85,204);background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"></span></u></p>

<p class="MsoNormal" style="text-align:justify;margin:0cm;line-height:115%;font-size:11pt;font-family:Arial,sans-serif"><span lang="EN-US" style="font-size:10pt;line-height:115%;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial">[2] Ellefsen, A. L., Æsøy, V.,
Ushakov, S., & Zhang, H. (2019). A comprehensive survey of prognostics and
health management based on deep learning for autonomous ships. IEEE
Transactions on Reliability, 68(2), 720-740</span></p>

<p class="MsoNormal" style="text-align:justify;margin:0cm;line-height:115%;font-size:11pt;font-family:Arial,sans-serif"><span lang="EN-US" style="font-size:10pt;line-height:115%;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial">[3] Floreano, D., & Wood, R.
J. (2015). Science, technology and the future of small autonomous drones. <i>nature</i>, <i>521</i>(7553), 460-466.</span></p>

<p class="MsoNormal" style="text-align:justify;margin:0cm;line-height:115%;font-size:11pt;font-family:Arial,sans-serif"><span lang="EN-US" style="font-size:10pt;line-height:115%;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial">[4] Aslansefat, K., Kabir, S.,
Abdullatif, A., Vasudevan, V., & Papadopoulos, Y. (2021). Toward Improving
Confidence in Autonomous Vehicle Software: A Study on Traffic Sign Recognition
Systems. <i>Computer</i>, <i>54</i>(8), 66-76.</span></p>

<p class="MsoNormal" style="text-align:justify;margin:0cm;line-height:115%;font-size:11pt;font-family:Arial,sans-serif"><span lang="EN-US" style="font-size:10pt;line-height:115%;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial">[5] Elghazel, W., Bahi, J.,
Guyeux, C., Hakem, M., Medjaher, K., & Zerhouni, N. (2015). Dependability
of wireless sensor networks for industrial prognostics and health management.
Computers in Industry, 68, 1-15.</span></p>

<p class="MsoNormal" style="text-align:justify;margin:0cm;line-height:115%;font-size:11pt;font-family:Arial,sans-serif"><span lang="EN-US" style="font-size:10pt;line-height:115%;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial">[6] Aizpurua, J. I., Catterson, V.
M., Papadopoulos, Y., Chiacchio, F., & Manno, G. (2017). Improved dynamic
dependability assessment through integration with prognostics. <i>IEEE Transactions on Reliability</i>, <i>66</i>(3), 893-913.</span><span lang="EN-US"></span></p><div><br></div>-- <br><div dir="ltr" class="gmail_signature" data-smartmail="gmail_signature"><div style="text-align:right;font-family:georgia,serif;color:rgb(51,0,153)"><i><b>Joxe Aizpurua.</b></i></div></div></div>