Applications are invited from interested and motivated candidates for the Junior Research Fellow (JRF) post in a CSIR-sponsored research
project for a temporary period, purely on a contractual basis, as per the following details.
Position: Junior Research Fellow (JRF).
Project title: Monitoring reproductive strategies of marsh crocodile populations within Gujarat, an interdisciplinary approach using deep learning
tools, behavioural observations and non-invasive endocrine assay.
Department: Biological and Life Sciences and School of Engineering and Applied Science, Ahmedabad University, Gujarat, India.
Project tenure: Three years (based on a performance review).
Job description: We are seeking a motivated and skilled Junior Research Fellow to join our team for an exciting project focused on developing
an animal identification algorithm.
The project involves processing drone footage of mugger crocodiles using deep learning techniques and
deploying the algorithm on Android OS mobile devices. The candidate will also work on model compression and initial deployment on Jetson
devices for experimentation.
Key responsibilities:
• Process and analyse video footage of mugger crocodiles captured by drones.
• Develop and implement deep learning
algorithms for animal identification.
• Work on model compression techniques to optimize algorithm performance.
• Deploy the developed
algorithm on Jetson devices for initial testing and experimentation.
• Develop the back-end of a mobile application for Android/iOS to deploy the
animal identification AI/ML model.
• Develop a responsive front-end UI of the app.
• Deploy the app to the Google Play store.
• Manage and
optimize GPU resources for efficient deep learning model training and inference.
If you are passionate about wildlife research and have the required skills, we encourage you to apply and contribute to this innovative project.
Refer to this citation below for more details.
Desai, B., Patel, A., Patel, V., Shah, S., Raval, M. S. and Ghosal, R. (2022) Identification of free-ranging mugger crocodiles by applying deep
learning methods on UAV imagery. Ecological Informatics, 101874.
Essential qualification: As per CSIR Guidelines for Research Scheme/Sponsored Schemes.
• B.S. 4 years program/B.Pharm./M.B.B.S./
Integrated B.S.-M.S./M.Sc./B.E./B.Tech. or equivalent degree, with 55% marks.
• Passing of NET/GATE test is mandatory.
Desired skills:
• Proficiency in Python programming.
• Experience with open-source deep learning libraries (e.g. TensorFlow, PyTorch).
• Knowledge of model compression techniques.
• Familiarity with deploying algorithms on embedded devices, particularly Jetson devices.
• Experience in developing mobile applications for Android/iOS.
• Familiarity with GPU handling and optimization for deep learning tasks.
Age limit: 28 years.
Age relaxation: The upper age limit is relaxable up to 5 years in the case of candidates belonging to scheduled castes/tribes/OBC, women and
physically handicapped candidates.
Fellowship: Rs 37,000 in the first and second years and Rs 42,000 in the third year upon performance review.
Application process: Please send in your updated CV with a cover letter to the following e-mail by 25 August 2024.
Professor Ratna Ghosal: ratna.ghosal@ahduni.edu.in.
Please include the following text in the subject line of your e-mail: ‘JRF Application for CSIR project’. The CV should include details of academic
record starting from 10th standard onwards with details of year of passing, university/college, etc. as well as work experience and nature of work,
if applicable.
Short-listed candidates will be informed by e-mail about the date of the interview
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