VIT Vellore Computational Biology, Life Sciences MSc JRF Job – Non-NET Can Also Apply
VIT Vellore Computational Biology, Life Sciences MSc JRF Job – Non-NET Can Also Apply. VIT Vellore MSc Life Sciences and Computational Biology Junior Research Fellow job opening. Interested and eligible applicants can check out all of the details on the same below
This job expires in
Applications are invited for the post of Junior Research Fellow (JRF) for an DST-SERB funded project entitled
Position: Junior Research Fellow (JRF)
No. of Positions: 1
itle of the Project: “Spatio-temporal distribution of microplastics, a vector in the sludge-laden soil environment – A mesocosm approach”
FILE NO.CRG/2021/001l33
Duration: 1 year
Sponsoring Agency: DST-SERB
Principal Investigator: Prof. Natarajan Chandrasekaran, Sr. Prof. Centre for Nanobiotechnology,
Co-Investigators: Dr. George Priya Doss, Associate Professor, Integrative biology Lab, School of Bioscience and Technology
How to Apply:
Send your resume along with relevant documents pertaining to the details of qualifications, scientific accomplishments, experience (if any) and latest passport size photo, etc. on or before (25/08/2023) through online http://careers.vit.ac.in.
- No TA and DA will be paid for appearing in the interview.
- Shortlisted candidates will be called for an interview at a later date, which will be intimated by email.
- The selected candidate will be expected to join at the earliest.
Qualification: Master’s Degree in Life science, with knowledge in Computational biology.
Added skills: Python and R program, NGS analysis such as WGS & WTS
Stipend: Rs. 31000 per month (consolidated) (For non-NET/GATE candidate, salary will be provided as per the institution norms)
Interview Questions for Junior Research Fellow (JRF) Position:
1. Question: Can you explain the focus and objectives of the DST-SERB funded project, “Spatio-temporal distribution of microplastics, a vector in the sludge-laden soil environment – A mesocosm approach”? Answer: The project aims to investigate the spatio-temporal distribution of microplastics in a soil environment contaminated with sludge. Using a mesocosm approach, we’ll study how these microplastics are dispersed over time and space. This research contributes to our understanding of environmental pollution and its potential impact.
2. Question: Could you elaborate on your experience and expertise in Computational biology, specifically related to the requirements of this project? Answer: I hold a Master’s Degree in Life Science, which has equipped me with a strong foundation in computational biology. I’ve also gained hands-on experience in utilizing Python and R programming languages for data analysis. Furthermore, I have a background in next-generation sequencing (NGS) analysis, particularly whole-genome sequencing (WGS) and whole-transcriptome sequencing (WTS).
3. Question: How would you approach the analysis of spatio-temporal data related to microplastics distribution in the sludge-laden soil environment? Answer: I would begin by collecting data at various time points and spatial locations within the mesocosm. Using Python and R, I would process and analyze the data, looking for trends and patterns in microplastics distribution. Statistical methods and visualization techniques would help me uncover insights into the dynamics of microplastics movement in the soil.
4. Question: Can you describe your familiarity with next-generation sequencing (NGS) analysis and its relevance to this project? Answer: NGS analysis, particularly WGS and WTS, is a valuable tool for studying genetic information on a large scale. In the context of this project, NGS analysis could help identify potential sources of microplastics and assess their interactions with soil microorganisms. My experience in NGS analysis enables me to extract meaningful insights from complex genetic data.
5. Question: In your opinion, how can the findings from this research contribute to addressing environmental challenges associated with microplastic pollution? Answer: The insights gained from this research can inform policies and practices aimed at mitigating the impact of microplastic pollution. Understanding the spatio-temporal distribution of microplastics in sludge-laden soil environments can guide waste management strategies and help prevent further contamination. By identifying high-risk areas and sources of microplastics, we can take proactive measures to protect our environment.
These interview questions aim to assess the candidate’s understanding of the project’s objectives, technical skills in computational biology and NGS analysis, as well as their ability to connect the research to broader environmental challenges. The provided answers offer insights into the candidate’s qualifications and approach to addressing the research objectives.
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