Qureos Mentor

King Abdullah University of Science and Technology

<div></div><div><div><div><div><div><div><div><div><div><div>King Abdullah University of Science and Technology: Faculty Positions: Computer, Electrical and Mathematical Science and Engineering Division (faculty): Statistics (faculty)
</div></div></div><div><div><h3 class="jobSectionHeader"><b>Location
</b></h3><div>KAUST, Saudi Arabia
</div></div><div><h3 class="jobSectionHeader"><b>Open Date
</b></h3><div>Feb 26, 2026
</div></div><div><h3 class="jobSectionHeader"><b>Deadline
</b></h3><div>Mar 28, 2026 at 11:59 PM Eastern Time
</div></div></div><div><div><h3 class="jobSectionHeader"><b>Description
</b></h3><div><div><div>The Computer, Electrical, and Mathematical Sciences and Engineering Division (https://cemse.kaust.edu.sa) at King Abdullah University of Science and Technology (KAUST) invites applications for a faculty position in the Statistics Program (STAT), at the rank of Research Assistant Professor or Research Associate Professor. The Statistics Program at KAUST educates students to analyze and model complex real-world problems arising in modern Statistical Data Science. We welcome applications in Artificial Intelligence, Anomaly Detection, and Intelligent Monitoring of Industrial and Environmental Systems focuses on advancing data-driven and model-based methods for fault detection, predictive maintenance, and process monitoring. The successful candidate will conduct research in data-driven and model-based methods for fault detection, predictive maintenance, and process monitoring, with applications in renewable energy, water and desalination systems, and industrial processes. The position involves developing advanced methods in machine learning, deep learning, multivariate statistical analysis, and explainable AI, and collaborating with academic and industrial partners.</div><br>
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Due to the high volume of applications received, only those submitted through the online Interfolio form will be considered. Applications will close on March 22, 2026.</div><br>
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Women and members of traditionally underrepresented minority groups are particularly encouraged to apply.</div><br>
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A successful candidate will be expected to contribute to research projects, supervise graduate students, publish in high-impact journals, and teach relevant courses at the graduate level. Faculty members enjoy secure research funding from KAUST commensurate with their level of experience and have opportunities for additional funding through several sources provided directly by KAUST, and through external sources including government organizations and industry.</div><br>
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KAUST (https://www.kaust.edu.sa) is an international, graduate-only research university, located on the shores of the Red Sea in Saudi Arabia. It has a diverse international community, with English as the official language. KAUST offers superb research facilities, including the upcoming Shaheen-3 supercomputer and a large-scale virtual reality installation; generous assured research funding; and internationally competitive salaries. KAUST attracts top international faculty, scientists, engineers and students to conduct curiosity-driven and goal-oriented research to address the world&rsquo;s pressing scientific and technological challenges. KAUST ranked 1st globally for citations per faculty for six consecutive years, was ranked the 1st University under 20 years old, and 7% of its faculty are listed as highly cited researchers (according to Clarivate). KAUST provides full financial support to its students, covering tuition, accommodation, and a living stipend. Additionally, it strives to drive regional innovation and economic development through its technology commercialization arm and numerous spin-off startups.</div><br>
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KAUST&rsquo;s award-winning campus has everything you need to live, work, study, and play. Designed to inspire and motivate our faculty, students and staff and their families to maintain an active lifestyle, KAUST is more than a university. With state-of-the-art fitness facilities, a golf course, numerous fine dining and casual fare restaurants, an Elementary and a Secondary school and the Red Sea just steps away, there is something for everyone (https://www.kaust.edu.sa/en/live).</div></div>
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</div></div><div><div><h3 class="jobSectionHeader"><b>Qualifications
</b></h3><div><div><div>We are particularly interested in candidates with educational backgrounds from distinguished institutions of higher learning or those who have previously contributed to such institutions. Ideal candidates will possess a Ph.D. in Statistics or a related field, exceptional research potential, the ability to attract external research funding, and a strong dedication to teaching. We offer competitive compensation, comprehensive employment benefits, and access to ample research funding opportunities to address industry-relevant projects. At KAUST, we embrace diversity and encourage applications from female faculty candidates. We are committed to cultivating a diverse faculty body and contributing to our vibrant academic community.</div></div>
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</div></div><div><div><h3 class="jobSectionHeader"><b>Application Instructions
</b></h3><div><div><div>You will be required to complete an application form and upload the following materials:</div><br>
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<ul><li>A complete curriculum vitae with a list of publications (and links to those)</li></ul>
<ul><li>Research statement and a teaching statement;</li></ul>
<ul><li>The names and contact information of at least 3 (and preferably 5) references.</li></ul><br>
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If more information is needed, please contact prof. Daniele Boffi, Associate Dean for Faculty, at the address below</div><br>
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daniele.boffi@kaust.edu.sa</div></div>
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</div></div></div><div><div><div><h3 class="jobSectionHeader"><b>Application Process
</b></h3><div>This institution is using Interfolio's Faculty Search to conduct this search. Applicants to this position receive a free Dossier account and can send all application materials, including confidential letters of recommendation, free of charge.</div></div></div></div></div></div></div></div></div></div><p></p>

Research Faculty Position in Statistics

<div></div><div><div><div><div><div><div><div><div><div><div>King Abdullah University of Science and Technology: Postdoc Positions: Physical Science and Engineering Division (postdoc)
</div></div></div><div><div><h3 class="jobSectionHeader"><b>Location
</b></h3><div>King Abdullah University of Science and Technology | Thuwal | KSA
</div></div><div><h3 class="jobSectionHeader"><b>Open Date
</b></h3><div>Feb 25, 2026
</div></div></div><div><div><h3 class="jobSectionHeader"><b>Description
</b></h3><div><div><p>The DeepWave industry-funded consortium is looking for two outstanding postdoctoral researchers to undertake impactful research on the development and application of cutting-edge machine (deep) learning numerical methods for wave-equation-based processing, imaging, and inversion.</p>
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Wave phenomena are ubiquitous in science, and they extend to objectives ranging from global Earth discovery, to natural resources exploration, to subsurface monitoring, as well as nondestructive testing and medical imaging. However, our current ability to create detailed images of the interior of such bodies from remote measurements and accurately invert for physical properties often lacks the accuracy and resolution we seek for making informed decisions. Both shortcomings are usually attributed to the limitations in our measurements and in the underlying physical models. Machine learning (ML) techniques can be exploited to identify common patterns in the data and augment the physical laws of wave propagation, leading in turn to improvements accuracy and resolution.</p>
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The selected candidate will join the research group of Prof. Tariq Alkhalifah within the Earth Systems Science and Engineering (ESSE) program at King Abdullah University of Science and Technology (KAUST), Saudi Arabia, and will work closely with other group members. The candidate will be expected to develop novel methodologies, validate their effectiveness using field data, and contribute to scaling these approaches to real-world applications in one or more of the following areas:</p>
<div><ul><li>Machine-learning-assisted subsurface characterization and monitoring</li></ul>
<ul><li>Distributed Acoustic Sensing (DAS) data processing and compression using ML</li></ul>
<ul><li>Physics-driven machine learning for geophysical modeling and inversion</li></ul>
</div><p>Further details can be found at: https://deepwave.kaust.edu.sa/research</p>
<p>Thus, the candidate is expected to have or about to have a PhD in a relevant topic, that includes geophysics, mathematics, physics, computer science or any related topics with a track record in relevant applications (processing, imaging and inversion).</p>
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<p>In addition to initiating, developing, and delivering high-quality research, collaborate with students, the candidate will be expected to publish in leading peer-reviewed journals, present at international conferences, and contribute to improving the quality and efficiency of the consortium code base. Preference will be given to candidates with a strong publication record and proven experience in Python programming, source code versioning and management, machine and deep learning, as well as a solid understanding of wave phenomena and geophysical data analysis and imaging.</p></div>
</div></div></div><div><div><h3 class="jobSectionHeader"><b>Qualifications
</b></h3><div><div><p>Basic Qualifications:</p>
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<li>A Ph.D. in Computational Geophysics, Computer Science, Applied Mathematics or similar field;</li>
<li>Portfolio of relevant publications;</li>
<li>Good programming skills in Python and proficiency in Torch and/or JAX;</li>
<li>Proficiency in written and spoken English.</li></ul><br>
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Differentiating Qualifications:</p>
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<li>Expertise in the development of seismic processing algorithms, high-performance computing, and/or large-scale inverse problems;</li>
<li>Experience in developing open-source software and a track record in collaborative software development.</li>
</ul></div></div></div></div><div><div><h3 class="jobSectionHeader"><b>Application Instructions<br>
</b></h3><div><div><div><div><p>Applications can be submitted by clicking on the &quot;Apply Now&quot; button.</p></div></div><br>
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</p></div></div></div></div></div><div><div><div><h3 class="jobSectionHeader"><b>Application Process
</b></h3><div>This institution is using Interfolio's Faculty Search to conduct this search. Applicants to this position receive a free Dossier account and can send all application materials, including confidential letters of recommendation, free of charge.</div></div></div></div></div></div></div></div></div></div><p></p>

Postdoctoral Fellow in the DeepWave Consortium

<div></div><div><div><div><div><div><div><div><div><div><div>King Abdullah University of Science and Technology: Postdoc Positions: Physical Science and Engineering Division (postdoc): Material Science and Engineering (postdoc)
</div></div></div><div><div><h3 class="jobSectionHeader"><b>Location
</b></h3><div>King Abdullah University of Science and Technology (KAUST)
</div></div><div><h3 class="jobSectionHeader"><b>Open Date
</b></h3><div>Feb 23, 2026
</div></div><div><h3 class="jobSectionHeader"><b>Deadline
</b></h3><div>Aug 22, 2026 at 11:59 PM Eastern Time
</div></div></div><div><div><h3 class="jobSectionHeader"><b>Description
</b></h3><div><div><div>We are seeking a skilled and motivated Field Technician with hands-on experience in medium-voltage systems, ideally gained through photovoltaic (PV) panel installation, commissioning, or maintenance. The role includes collecting data in farm fields to monitor crop growth using IR camera&ndash;mounted drones.<b> </b>This role is suited for candidates who enjoy dynamic field work, technical challenges, and contributing to advanced energy and inspection projects.</div><br>
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Key Responsibilities</b></div>
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<li>Perform field measurements, testing on PV panels and medium-voltage electrical systems.</li>
<li>Carry out farm-based field work to collect data for smart agriculture projects</li>
<li>Conduct remote inspections, including drone-assisted surveys (<b>commercial drone pilot license is a strong plus</b>).</li>
<li>Safely lift, move, and position PV panels and related equipment for measurement and inspection tasks.</li>
<li>Working with researchers and graduate students to collect data for their projects related to PV and smart agriculture.</li>
<li>Assist with lab-based activities, lab safety, equipment maintenance, experiments, and testing protocols as assigned.</li>
<li>Follow all safety procedures and maintain proper documentation of field and lab work.</li>
<li>Support setup, maintenance, and operation of field instrumentation and monitoring equipment.</li></ul><br>
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Why Join Us?</b></div>
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<li>Work on cutting-edge renewable energy and remote inspection research projects.</li>
<li>Opportunity to grow your technical skillset across field, lab, and drone-based operations.</li>
<li>Supportive environment with strong commitment to safety and innovation.</li>
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</b></h3><div><div><ul><li>Technical diploma or degree in Electrical Engineering, Electromechanics, Renewable Energy, or related field.</li>
<li>Proven experience with medium-voltage systems.</li>
<li>Familiarity with PV installation, troubleshooting, or commissioning.</li>
<li>Ability to safely handle and lift moderate weights on a routine basis (e.g., PV modules, tools, and sensitive equipment).</li>
<li>Strong interest in field operations, hands-on technical work, and outdoor activities.</li>
<li>Candidates must be proficient in both English and Arabic, spoken and written.</li></ul><br>
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Preferred Qualifications</b></div>
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<li>Commercial drone pilot license (e.g., GACA Part 107 Commercial Drone Operator License).</li>
<li>Experience in remote inspection using drones, thermography, or aerial imaging.</li>
<li>Basic experience with laboratory equipment or electrical testing tools.</li></ul><br>
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Soft Skills</b></div>
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<li>Strong problem-solving abilities and attention to detail.</li>
<li>Good communication in English and teamwork skills.</li>
<li>Willingness to learn, adapt, and support multidisciplinary project teams.</li>
</ul></div></div></div></div></div><div><div><div><h3 class="jobSectionHeader"><b>Application Process
</b></h3><div>This institution is using Interfolio's Faculty Search to conduct this search. Applicants to this position receive a free Dossier account and can send all application materials, including confidential letters of recommendation, free of charge.</div></div></div></div></div></div></div></div></div></div><p></p>

Field Technician (Medium Voltage, Remote Sensing & Labs)

Join King Abdullah University of Science and Technology and explore 3   exciting career opportunities. They're hiring for various roles with options for remote or on-site work. Apply today and become part of their innovative team.

King Abdullah University of Science and Technology

About Company

Research Faculty Position in Statistics

Postdoctoral Fellow in the DeepWave Consortium

Field Technician (Medium Voltage, Remote Sensing & Labs)