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University of Hyderabad Project Associate Recruitment 2025
Hi friends 👋
Great news for those in search of research-oriented government jobs! The University of Hyderabad (UoH) has announced a recruitment drive for the position of Project Associate in a funded research project titled “Forecasting dengue outbreaks using ensemble machine learning techniques.” This is an excellent opportunity for graduates in Computer Science and Information Technology who are passionate about Machine Learning and research careers.
In this article, I’ll provide all the essential details regarding the job so that you don’t miss any crucial information.
Job Overview
| Details | Information |
|---|---|
| Job Role | Project Associate |
| Organization | University of Hyderabad |
| Qualification | B.Tech / M.Tech (CS/IT or related) |
| Experience | Not required |
| Salary | ₹30,000 per month |
| Job Type | Temporary (Project-based) |
| Location | Hyderabad, Telangana |
| Skills Required | Machine Learning, Deep Learning, Python |
About the University
The University of Hyderabad is a prominent central university recognized for its research excellence in India. This recruitment falls under the School of Computer and Information Sciences, where candidates will have the chance to gain hands-on experience in real-time data science and health-related research projects.
Job Role
Position Details
Post Name: Project Associate
Project Title: Forecasting dengue outbreaks using ensemble machine learning techniques
Tenure: 1 year (extendable based on performance)
Educational Qualifications
Candidates must possess:
- B.Tech / M.Tech in:
- Computer Science
- Computer Engineering
- Information Technology
- Related disciplines
Additionally, a strong knowledge of:
- Machine Learning
- Deep Learning
- Python programming
- Good communication skills in English
Vacancy
Total Vacancies: 01 post only
Salary and Benefits
Monthly Stipend: ₹30,000
House Rent Allowance: Not applicable (NIL)
Travel Allowance: No TA/DA will be paid for interview or joining
Age Limit
Maximum Age: 30 years (as per notification)
Job Responsibilities
As a Project Associate, your tasks will include:
- Developing machine learning models for forecasting disease outbreaks.
- Analyzing datasets related to dengue outbreaks.
- Contributing to research papers and technical documentation.
- Assisting the project investigator in research activities.
Other Benefits
- Work within a prestigious central university environment.
- Gain practical experience in AI & Machine Learning.
- Enhance your research profile.
- Valuable addition for those considering PhD or research careers.
Selection Process
The selection will follow these steps:
- Shortlisting of applications
- Written test / Skill test / Interview (if required)
👉 Only shortlisted candidates will be informed via email or letter.
How to Apply
👉 FIRST STEP: CLICK THE APPLY LINK PROVIDED (or download the official application format from the notification)
Follow these steps carefully:
- Download and fill out the Form-B application format.
- Attach self-attested copies of:
- Educational certificates
- Age proof
- Experience certificates (if any)
- Mention Project Number: ANRF/PAIR/2025/000012/EPAIR/Task-24 Dt: 20-09-2025 on the cover.
- Send the completed application to:
The Dean,
School of Computer and Information Sciences,
University of Hyderabad,
Prof. C.R. Rao Road, Gachibowli,
Hyderabad – 500046
📧 You may also email the scanned application to: rajendraprasad@uohyd.ac.in
🗓 Last Date to Apply: Refer to the notification (apply as early as possible).
Important Note
This position is purely temporary, and no claim for a permanent job at UoH will be entertained. There is no application fee required.
Final Words
If you possess skills in Machine Learning and Python and are eager to work on a real-world health research project, then the University of Hyderabad Project Associate Recruitment 2025 is an incredible opportunity. Don’t hesitate—apply early to kickstart your research career! 🚀
Important Links
Disclaimer: We do not charge any fees for this information. This content is for informational purposes only, and details have been gathered from official sources.