Post Doctoral Positions

Post Doctoral Positions

Middle East Technical University, Northern Cyprus Campus, promotes diversity in its hiring, promotion, and development of its personnel and does not discriminate on the basis of race, sex, color, national origin, religion, marital status or disability.

Thank  you for your interest in Post-Doctoral  Positions at the
  Middle  East Technical University, Northern Cyprus Campus

Applications are currently being requested  in the following fields and areas:

1. Computer Engineering/Computer Science, “STA-DS: Scanpath Trend Analysis on Dynamic Visual Stimuli”

   Scanpath Trend Analysis (STA) has been developed to identify a single representative path (namely, trending path) for multiple scan paths (i.e. eye-movement sequences) of eye-tracking data collected from different users. STA has been used for various purposes, including autism detection, web-page transcoding, analysis of novice programmers’ behaviors, and human activity recognition. However, the current version focuses on eye tracking data recorded on static stimuli, not dynamic visual stimuli, particularly videos, thus limiting its application areas. In particular, for autism detection, dynamic visual stimuli are a critical aspect of the classification of users. This project aims to enable STA to work with dynamic visual stimuli. It will explore artificial intelligence techniques, particularly machine vision algorithms, to detect and track objects on videos and integrate these objects into STA to process individual scan paths and create a trending path based on these objects. The project will also evaluate the results of STA with dynamic visual stimuli by considering the previous results achieved with static visual stimuli as a baseline. Additionally, it will investigate whether STA is as successful with dynamic visual stimuli for autism detection as it is with static visual stimuli.

    

   For more information, you can contact:
   Assist. Prof. Dr. Şükrü Eraslan seraslanmetu.edu.tr, Assist. Prof. Dr. Meryem Erbilek merbilekmetu.edu.tr, Prof. Dr. Yeliz Yeşilada yyelizmetu.edu.tr

    

2. Computer Engineering/Computer Science, “Intelligent 5G-Enabled Communication Systems for Smart Cities and Disaster Resilience”

   The rapid evolution of 5G, federated learning (FL), and AI-driven decision-making frameworks, including Large Language Models (LLMs) and Visual Language Models (VLMs), is transforming disaster resilience and emergency communication networks. This research explores integrating 5G-powered ultra-reliable low-latency communication (URLLC), federated learning-driven edge AI, and UAV-assisted networking to develop scalable, privacy-preserving, and resilient post-disaster communication infrastructures. The proposed system ensures real-time connectivity restoration in disaster-affected regions by leveraging UAV-based solutions, 5G communication, and intelligent network adaptation through AI. LLM based solutions are considered to introduce improved situational awareness by analyzing multimodal sensor data and coordinating emergency response strategies, while VLMs process visual inputs from surveillance for rapid damage assessment. This approach provides an adaptive, AI-driven communication framework designed to bridge connectivity gaps, optimize resource allocation, and improve emergency response effectiveness in disaster-stricken areas. Federated learning at the 5G edge enables real-time situational awareness and GDPR-compliant AI-driven analytics, allowing distributed AI models to train locally on IoT devices without exposing raw data. This preserves privacy while optimizing disaster mitigation strategies and emergency resource allocation. The proposed system also integrates UAV-enabled aerial relays and self-healing AI-driven mesh networks to ensure uninterrupted connectivity in disaster zones, enhancing real-time urban resilience analytics, predictive disaster modeling, and autonomous emergency coordination. By integrating LLMs and VLMs into next-generation AI-driven communication systems, this study provides a paradigm shift in secure urban communication, ensuring future-proof smart infrastructures that dynamically adapt to evolving threats, technological advancements, and large-scale disaster events in the 5G and beyond era.
    

   For more information, you can contact:
   Assist. Prof. Dr. Muhammad Toaha R. Khan khanmetu.edu.tr, Assist. Prof. Dr. Mariem Hmila mariemmetu.edu.tr, Prof. Dr. Enver Ever eevermetu.edu.tr

    

3. Aerospace Engineering, “Aerodynamic Flow Control with Passive and Active Flow Control Techniques”. The project (s) will focus on emission (CO, CO₂, Nox etc.) reduction by using aerodynamic flow control of aeronautical and road vehicles depending on the candidate's previous experience and will be decided with mutual agreement. The candidate should hold a Ph.D. in Aeronautical/Aerospace/Mechanical Engineering and should be experienced in experimental aerodynamics and/or computational fluid dynamics. The project can be either experimental or numerical (CFD) based on the candidate's experience.

    

   For more information, you can contact:
   Dr. Baris Gungordu, Aerospace Engineering Program, gbarismetu.edu.tr

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The documents listed below should be submitted electronically to Dr. Murat Fahrioğlu, at fmuratmetu.edu.tr. Documents faxed or sent by mail will not be taken into consideration:  
  
Cover letter,   
  
Letter of intent explaining the expected  contribution of the collaborative research to the field,  
  
Curriculum vitae,  
  
List of publications,  
  
List of citations,  
  
Copies of previous titles/degrees  awarded.