National University of Sciences & Technology

Event Category: Vacancy

Apply for the position of Research Assistant (Machine Learning & Wireless Communication) under the NUST-funded project titled “AI-Driven Optimization Techniques for Next-Generation Wireless Communication Systems.”

Duration: 10 Months

Responsibilities:

  1. Design, train and deploy lightweight deep learning models for real-time signal processing and channel estimation.
  2. Conduct simulations, model development and performance evaluation on conventional and edge computing platforms.
  3. Optimize CNN models for quantization and edge deployment (Jetson, Raspberry Pi).
  4. Implement and test signal processing and noise modeling frameworks.
  5. Prepare detailed project documentation and technical reports.

Qualifications:
The ideal candidate will hold a BS in Computer Science, Software Engineering, or a related discipline (with a strong background in ML/DL) or MS in Computer Science, Computer Engineering, Data Science, or AI (with research focus on signal processing, communications, or machine learning).

Preferred Skills:

  • Proficiency in Python and deep learning frameworks (TensorFlow / PyTorch / Keras)
  • Knowledge of wireless communication systems (5G, SISO/MIMO, channel estimation)
  • Experience with MATLAB or Python-based communication simulations
  • Familiarity with CNN model design, quantization (FP32, FP16, INT8)
  • Understanding of embedded inference deployment (TensorRT, ONNX)
  • Strong grasp of data handling, training pipelines, and performance benchmarking (NMSE, latency)

Application Procedure:
Interested candidates are invited to submit their CV (including CGPA, relevant projects, research experience, and skillset) at [email protected] with the subject line “NUST Funded Project – Research Assistant (Satellite 5G CNN)”

Deadline: November 6, 2025

Apply for the position of Research Associate under the funded project titled “Design and Development of Technology Demonstrator of Morphing Wing for Aerial Vehicles.”
 
Duration: 1.5 Years
 
Responsibilities:
  1. Conduct comprehensive literature review and feasibility study
  2. Perform 3D modelling of complex aerodynamic structures
  3. Carry out high-fidelity transient simulations
  4. Implement data quality checks and validation processes
  5. Prepare project documentation and technical reports
 
Qualifications:
The ideal candidate will hold a Bachelor’s degree in Aerospace Engineering, Mechanical Engineering, or a related field (Master’s preferred) from an HEC-recognized institution and possess strong technical, analytical and report-writing skills, along with knowledge of propeller design and the ability to work independently.
 
Application Procedure
Interested candidates are invited to submit their CV at [email protected] with the subject line “Application – Research Associate (Morphing Wing Project)”
 
Deadline: October 30, 2025
Exciting opportunities are available for Postgraduate Students and Research Associates under the projects “Shielding HAPS Against Intelligent Link-Level Attacks (SHAILLA)” and “Design of Ambient Backscatter Communications (DABICSE)”
 
The projects focus on the security of High-Altitude Platform Station (HAPS) systems and the design of ambient backscatter communication techniques. The research will identify vulnerabilities, develop intelligent attack models, and design robust countermeasures.
 
Positions Available:
2× Postgraduate Students (MS/PhD candidates)
1× Research Associate (NATO-funded)
1× Research Associate (PSF-funded)
 
Eligibility & Desired Skills
1. Background in Electrical/Electronics/Telecom/Computer Engineering (or related fields)
2. Strong grasp of wireless communications, physical layer concepts, and network security
3. Experience with MATLAB, Python, or SDR platforms (e.g., USRP)
4. Familiarity with AI/ML techniques (reinforcement learning, anomaly detection) is a plus
 
Benefits
1. Opportunity to contribute to cutting-edge 6G security research
2. Work alongside experienced faculty and researchers at SEECS, NUST
3. Stipend as per NUST and project funding guidelines
4. Publication and international collaboration opportunities
 
Application Procedure
Interested candidates are encouraged to send their CV and a brief Statement of Interest (max 1 page) to [email protected]
 
Deadline: October 5, 2025 (Please mention the position you are applying for in the subject line.)

Exciting opportunity available for a Research Assistant under the project “AI-Driven Optimization for 5G over Satellite Networks”.

Position: Research Assistant
Duration: 10 Months
Host Institution: NUST-SEECS

Project Overview
The project aims to adapt the 5G protocol stack for satellite communication by developing a hardware-accelerated testbed using an AI-SDR platform. It addresses key challenges including long delay and low bandwidth in satellite links.

Responsibilities

  • Assist in setting up and configuring the 5G network simulator
  • Modify OAI protocol stack parameters for satellite link conditions
  • Support integration and testing with SDR hardware
  • Conduct performance tests and document results

Qualifications

  • Enrolled in MS (EE, Software Engineering or Computer Science)
  • Strong background in AI and Edge Computing
  • Proficiency in C/C++ and Python
  • Familiarity with Linux
  • Basic knowledge of wireless communication principles

Application Procedure
Submit CV, academic transcript and a brief statement of interest to [email protected]

Deadline: October 1, 2025

For queries, contact Mr. Bilal at +92 306 2319030

Join Us at NUST!
 
Exciting opportunities are available under the project “Security Framework for the Internet of Things: Ensuring Data Integrity and Malicious Node Detection”, hosted jointly by NUST, FAST-NUCES and Istanbul Medipol University, Türkiye.
 
Project Overview:
The project proposes a novel Secure Integrated Sensing and Communication (ISAC) framework to address pressing IoT security challenges, focusing on data integrity, device authentication and malicious node detection. Leveraging physical layer attributes (RSSI, CSI, ToF), it ensures lightweight, real-time trust evaluation with scalability and low latency, advancing beyond conventional cryptographic solutions.
 
Available Positions:
  1. Graduate Student (24–36 Months)
  2. Research Assistant (24–36 Months)
Qualification:
  • PhD or MS in Electrical/Computer Engineering, Computer Science, or Cybersecurity
  • Strong background in IoT security, wireless communications, and access control mechanisms
  • Proficiency in Python/MATLAB, with experience in network simulators and probabilistic models
  • Familiarity with Zero Trust, blockchain or federated learning approaches will be an advantage
Application Procedure:
Interested candidates should submit CV, Publication list and Cover letter to [email protected] with the subject line: “Graduate Student – NATO” (for Graduate Student position) or “Research Assistant – NATO” (for Research Assistant position)
 
Deadline: September 28, 2025
 
For queries, please contact Dr Mohsin Kamal at +92 51 90852128.

Duration: 24 Months
Number of Positions: 01
Application Deadline: September 15, 2025

NUST, Pakistan in collaboration with Gazi University, Türkiye, is seeking a dedicated Research Fellow to work on the project “IoT Cybersecurity Augmentation Using Deep Learning-Aided RF Fingerprinting for Next-Gen IoT Authentication.” The project aims to develop a non-cryptographic cybersecurity solution using Deep Learning-aided Radio Frequency Fingerprinting (DL-RFF) for IoT and 6G networks.

Key Responsibilities:

  • Contribute to SDR-based testbed design, signal acquisition and pre-processing in GNU Radio/MATLAB
  • Design and optimize lightweight DL models (e.g., CNNs, ResNet) for RF fingerprinting and rogue device detection
  • Address operational challenges (low SNR, receiver-dependency) while optimizing accuracy, openness and latency (<2 sec)
  • Support hardware implementation on ADRV9361-Z7035 FPGA-ARM platform for edge deployment

Eligibility Criteria:

  • PhD or Master’s (with significant experience) in Electrical/Computer Engineering or Telecommunications
  • Strong background in wireless communications, DSP and physical layer security
  • Proficiency in Python and MATLAB; experience with TensorFlow/PyTorch
  • Familiarity with SDRs (GNU Radio)

How to Apply:
Interested candidates should email their CV, publication list and cover letter to [email protected] with the project title in the subject line.

For Queries: Contact Mr Bilal at +92 306 2319030

Exciting opportunities are available for multiple research positions in the grant entitled HEC TDF Project Entitled “Development of an elastomer-based microbubble contrast agent to produce local cost-effective and improved technology for diagnostic and clinical uses”.
 
Available Positions:

1. Research Assistant (01 Vacancy, Contract)

    • Minimum qualification: MS degree
    • Previous experience in ultrasound imaging and/or nanotechnology will be preferred
    • Duration: 2 years

2. PhD Studentship (01 Vacancy)

    • Must be enrolled in a PhD programme (research phase or about to begin)
    • Supervised by Dr Shah Rukh Abbas
    • Previous experience in ultrasound imaging and/or nanotechnology will be preferred
    • Duration: 2 years
3. MS Studentship / Research Assistant (02 Vacancies)
    • Must be enrolled in an MS degree programme (coursework completed and entering research phase)
    • Supervised by Dr Shah Rukh Abbas
    • Prior theoretical knowledge or research experience in ultrasound imaging and/or nanotechnology will be preferred
    • Duration: 2 years
4. Postdoctoral Fellowship (01 Vacancy)
    • PhD degree completed
    • Duration: 6 months (full-time) or 12 months (partial)
Application Procedure
Applicants are required to submit their CV, academic degrees, experience letters and a personal statement via email to [email protected]
 
Deadline for applications: September 7, 2025
 
For more information, contact Dr Shah Rukh Abbas at [email protected] or 051-90856125/ 0335-5449622

Applications are open for the post of Research Assistant under the project “Sustainable Crop Residue Management for Climate Resilience in Pakistan” at NUST-ASAB.

Position Details

Vacancy: 01 (Contract, 3 Months)

Qualification: MS in Biological Sciences, Agricultural Sciences, Plant Sciences, or a relevant field

Requirement: At least one peer-reviewed publication involving Life Cycle Assessment (LCA)

How to Apply
Submit a one-page application, CV, and supporting documents to: [email protected]

Deadline: September 10, 2025

SINES at NUST is seeking a highly motivated and skilled Research Associate (Software Engineer) to contribute to the design and development of a centralized biomedical database and management system. The role focuses on front-end development with integration of Electronic Health Records (EHR) and standardized data modeling.
Duration: 1 Year
Number of Positions: 01
Application Deadline: August 10, 2025
 
Key Responsibilities:
  • Design data storage architecture and specify technical requirements
  • Standardize data models and coding for uniform representation
  • Develop ETL processes for EHR data consolidation
  • Integrate multiple EHR systems into a unified repository
  • Ensure data quality through validation and accuracy checks
 
Eligibility Criteria:
AI Experience with CS/SE Background, Biomedical Familiarity Preferred
 
How to Apply:
Interested candidates should email their CV to [email protected]

Vacancy Announcement!

Join Our Team at the Robotics and Machine Intelligence (ROMI) Lab, SEECS, NUST!

Position: ML Research Associate
Category: Research & Development
Duration: 6 Months
Number of Openings: 03

Eligibility Criteria:

Qualification:
– MS in Computer Science (CS), Electrical Engineering (EE)
– Software Engineering (SE), or a related field.

Requirements:
– Technical Expertise: Strong knowledge of machine learning, deep learning, robotics, and 3D data analysis. Experience with web scraping is a plus.
– Programming Skills: Proficiency in Python, PyTorch, and deep learning models, particularly for time-series data.

How to Apply:
Email: [email protected]

Last Day to Apply: February 7, 2025