Advertisement for the post of Junior Research Fellow / Project Associate-I

Pandit Deendayal Energy University (PDEU) is looking for meritorious young researchers for the post of Junior Research Fellow (01)
or Project Associate-I (01) Post for the project titled “Synergistic effect of Triboelectrification at Liquid-Solid Interface and Machine Learning techniques for smart healthcare systems” sponsored by Anusandhan National Research Foundation, Advanced Research Grant (ARG) Program.

Essential Qualification:

Master’s Degree in Engineering / Technology

OR

Bachelor’s degree in Engineering / Technology from a recognized University or equivalent.

For JRF, a valid NET/GATE is essential.

The upper age limit: As per ANRF rules

Additional Skills: 

·  Python programming, ML and Deep Learning, MLX, Pytorch / Tensorflow, image processing and/or computer vision algorithms, SkLearn.

Duration of appointment:  12 months (may be extended as per requirement or till project completion, based on performance).

Last date of Application

30th June, 2026

Tentative Interview Date

06th July, 2026

Email ID for Applying

Mohendra.roy@sot.pdpu.ac.in ; Mohendra.roy@ieee.org 

Fellowship: - As per ANRF norms.

Fellowship (as per funding agency norms)

Category:

Junior  Research  Fellow (JRF)

As per ANRF,ARG norms

@ Rs.37,000 + 30% HRA (per month)

Project Associate-I (PA-I)

@ Rs. 30,000 + 30% HRA (per month)

Please note that your CV should clearly mention contact details (address, phone no, email ID), date of birth, qualifications, and details of experience (with the name of the organization/institute).

Only Shortlisted candidates will be called for an interview through email. Offer of fellowship is purely contractual and limited to the project for the project duration only as per funding agency norms, and does not confer any right to the selected candidate for absorption in Pandit Deendayal Energy University.

Candidates are required to produce all certificates/testimonials in original at the time of the interview.

No TA/DA will be paid for attending the interview.

 ## About the Project

The project, **"Synergistic Effect of Triboelectrification at Liquid-Solid Interface and Machine Learning Techniques for Smart Healthcare Systems,"** aims to develop next-generation intelligent biomedical sensing systems by integrating advanced triboelectric sensor technologies with Artificial Intelligence and Machine Learning.

The sensor development team will design and fabricate novel **Triboelectric Nanogenerator (TENG)-based biomedical sensors** capable of capturing electrical responses generated at liquid-solid interfaces. These sensors will primarily be investigated for the analysis of biological fluids such as sweat and glucose-containing samples, with the long-term objective of enabling non-invasive and smart healthcare monitoring systems.

A key scientific goal of the project is to understand the complex interaction mechanisms occurring at the liquid-solid interface and correlate sensor responses with clinically relevant physiological parameters such as glucose concentration, electrolyte levels, and other biochemical indicators.

The project will generate large volumes of sensor data under varying environmental and biological conditions. This data will serve as the foundation for developing intelligent AI-driven models capable of automatically interpreting sensor responses and converting them into meaningful healthcare information.

## Expectations from the JRF / Project Associate (AI/ML)

The selected candidate will be an integral member of the Artificial Intelligence and Data Analytics team and will be expected to:

### Research and Development Responsibilities

* Develop AI, Machine Learning, and Deep Learning algorithms for analyzing triboelectric sensor data.

* Design data preprocessing, feature extraction, and signal analysis pipelines for sensor outputs.

* Develop predictive models to estimate physiological parameters such as glucose levels and sweat electrolyte concentrations from raw sensor responses.

* Build explainable and interpretable AI models that can translate complex sensor signals into clinically meaningful values.

* Perform statistical analysis, validation, and performance evaluation of developed models.

* Work closely with the sensor fabrication team to understand sensor characteristics and optimize data collection protocols.

* Contribute to the development of intelligent healthcare monitoring platforms and decision-support systems.

### Technical Skills Expected

* Strong programming skills in Python.

* Experience with Machine Learning and Deep Learning frameworks such as PyTorch and TensorFlow.

* Knowledge of data analytics, signal processing, and pattern recognition.

* Familiarity with Scikit-learn and modern AI development tools.

* Experience in handling time-series, sensor, or biomedical data will be highly advantageous.

* Knowledge of Explainable AI (XAI), multimodal learning, or healthcare AI will be considered an added advantage.

### Academic Expectations

The candidate is expected to actively participate in:

* Publishing research papers in reputed journals and conferences.

* Patent drafting and technology development activities.

* Preparation of project reports and technical documentation.

* Collaborative interdisciplinary research involving AI, biomedical sensing, healthcare technologies, and electronics.

This position is particularly suitable for candidates interested in pursuing a Ph.D. in Artificial Intelligence, Biomedical Engineering, Healthcare Informatics, or related interdisciplinary domains in the future.

More about the Research Group can be found at:

https://sites.google.com/view/mohendraroylab/home?authuser=0