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Ph.D. Position in Computer Science (Wearable Intelligence & Data Fusion)
<p>Constructor University in collaboration with Constructor Knowledge Labs and Constructor Technology</p>
<p><strong>About the Position</strong></p>
<p>The research group of <a href="https://sari-saba-sadiya.github.io/">Dr. Sari Sadiya</a> at <strong>Constructor Knowledge Labs (CKL)</strong>, in collaboration with <strong>Constructor University (CU)</strong> and <strong>Constructor Technology (CT)</strong>, invites applicants for <strong>Ph.D. student positions</strong> in Computer Science with a focus on <strong>wearable intelligence, multimodal data fusion, and edge AI</strong>.</p>
<p>The project investigates how wearable data streams can be transformed into structured knowledge and integrated into a knowledge-grounded digital avatar that supports bi-directional collaboration in education and research.</p>
<p>Ph.D. students will work in a highly interdisciplinary environment, combining <strong>AI/ML, edge computing, cognitive science, and human–computer interaction</strong>. In close collaboration with academia and industry, they will contribute to building <strong>privacy-preserving, real-time personalization frameworks</strong> while pursuing their doctoral dissertation.</p>
<p><strong>About the Program</strong></p>
<p>The PhD program is research-centered, emphasizing original contributions in:</p>
<ul>
<li><strong>Wearable data analytics and fusion methods</strong></li>
<li><strong>Biomedical data analytics</strong></li>
<li><strong>On-device processing and performance modeling</strong></li>
<li><strong>Personalization and adaptive reasoning systems</strong></li>
<li><strong>AI for Education</strong></li>
</ul>
<p>Doctoral students will also have access to specialized courses in:</p>
<ul>
<li>Artificial Intelligence, Machine Learning, and Edge Computing</li>
<li>Advanced Computational Methods and Data Science</li>
<li>Cognitive Science and Human-Centered Computing</li>
</ul>
<p>As part of the program, students will collaborate with <strong>Constructor Technology</strong> to gain first-hand industrial experience, contributing to real-world testbeds and prototypes.</p>
<p><strong>Research Focus</strong></p>
<p>This PhD position is part of the <strong>Wearable Intelligence Project</strong>, with two main research directions:</p>
<ul>
<li><strong>Data fusion of heterogeneous temporal streams</strong></li>
<ul>
<li>Designing algorithms to unify multimodal signals (physiological, cognitive, contextual, scheduling, and learning data).</li>
<li>Developing pipelines that produce structured insights powering the <strong>Agentic Personalization Engine (APE)</strong>.</li>
</ul>
<li><strong>On-device data processing &amp; performa