VIT Vellore Scientist Job For PhD Bioinformatics, Comp Bio, Biotech & Life Sciences

VIT Vellore Scientist Job For PhD Bioinformatics, Comp Bio, Biotech & Life Sciences

VIT Vellore Scientist Job For PhD Bioinformatics, Comp Bio, Biotech & Life Sciences. PhD Bioinformatics/ Computational Biology/ Biotechnology/ Microbiology/Life-sciences vacancy is available at the Vellore Institute of Technology. Interested and eligible applicants can check out all of the details on the same below

Possible Interview Questions for the Scientist-B Position are posted below

This job expires in

Applications are invited for the Post of Scientist-B for the ICMR Funded Project at Vellore Institute of Technology (VIT), (BMI/12(61)/2022 – IRIS ID: 2021-10630), Vellore Institute of Technology (VIT).

Job Title: Scientist-B

Title of the Project: “The effect of acquired bacterial mutations on metabolism and fitness of multi-drug resistant pathogenic bacteria by genomics, systems biology and machine learning approaches”

Sponsoring Agency: ICMR, Government of India.

Duration: 3 Years

Principal Investigator: Dr. Anand Anbarasu, Professor, Department of Biotechnology, School of Biosciences & Technology, Vellore Institute of Technology (VIT), Vellore – 632 014, Tamil Nadu

Co-Principal Investigator: Dr. Sudha Ramaiah, Professor, Department of Biosciences, School of Biosciences & Technology, Vellore Institute of Technology (VIT), Vellore – 632 014, Tamil Nadu

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 (21/07/2023) through online http://careers.vit.ac.in

• No TA and DA will be paid for appearing the interview.
• Shortlisted candidates will be called for an interview after last date of submission.
• The selected candidate will be expected to join at the earliest.

Qualification: PhD in Bioinformatics/Computational Biology/Biotechnology/ Microbiology/Life-sciences.

Desirable: Candidates having knowledge in Systems biology, MD simulations, Linux, machine learning will be given preference.

Stipend: Rs. 48,000/ + 10% HRA – per month (two years) and Rs. 48,000/+ HRA – per month.

View Notification 

Possible Interview Questions for the Scientist-B Position:

1. Can you explain your experience and expertise in the field of bioinformatics and computational biology? How have you applied your skills to previous research projects?
   • Answer: I have completed my PhD in Bioinformatics and have hands-on experience in analyzing biological data using various computational tools and algorithms. During my research, I have worked on projects involving genomics, transcriptomics, and proteomics data analysis, where I applied statistical methods and machine learning techniques to derive meaningful insights and identify potential biomarkers.
2. The project focuses on studying the effect of acquired bacterial mutations on metabolism and fitness of multi-drug resistant pathogenic bacteria. How would you approach this research topic using genomics, systems biology, and machine learning approaches?
   • Answer: To address this research topic, I would first collect genomic data from both drug-resistant and drug-sensitive strains of bacteria. I would then analyze the genetic variations using bioinformatics tools and identify specific mutations associated with drug resistance. Integrating this information with systems biology techniques, I would study the metabolic pathways affected by these mutations and investigate their impact on bacterial fitness. Machine learning algorithms can be employed to develop predictive models for understanding the relationship between genetic changes, metabolic alterations, and bacterial fitness.
3. Have you worked with MD simulations and Linux in your previous research? Can you provide an example of how you utilized these tools to address a scientific question?
   • Answer: Yes, I have experience with MD simulations and Linux. In one of my projects, I investigated the protein-ligand interactions of a potential drug target using MD simulations. I performed molecular dynamics simulations to study the conformational changes and binding affinity of the protein-ligand complex. Linux was utilized for running the simulations and analyzing the trajectory data. Through this study, we gained insights into the binding mechanism and identified key residues responsible for the interaction, which contributed to the rational design of novel drug candidates.
4. The job description mentions knowledge in machine learning as desirable. Can you provide an example of how you have applied machine learning techniques in your previous research?
   • Answer: In my previous research, I utilized machine learning algorithms to predict protein-protein interactions. I collected a large dataset of protein sequences and experimentally verified interactions. By training the machine learning model using this dataset and incorporating features such as sequence similarity, physicochemical properties, and structural information, I developed a predictive model that could accurately identify potential protein-protein interactions. This approach helped in understanding protein networks and uncovering novel protein interactions that play crucial roles in biological processes.
5. How do you plan to contribute to this research project and what are your expectations from this role as a Scientist-B?
   • Answer: As a Scientist-B, I aim to bring my expertise in bioinformatics, computational biology, and systems biology to contribute towards understanding the effect of acquired bacterial mutations on drug resistance and bacterial fitness. I plan to employ advanced computational methods, integrate multi-omics data, and leverage machine learning techniques to unravel the underlying mechanisms. I look forward to collaborating with the research team, publishing high-impact research articles, and making significant contributions to the field of microbial genomics and drug resistance.

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