Bioinformatics Programming Associate Job For MSc, MTech & PhD – Bioinformatics, Comp Biology Apply at AcrannoLife Genomics

Bioinformatics Programming Associate Job For MSc, MTech & PhD – Bioinformatics, Comp Biology Apply at AcrannoLife Genomics

Bioinformatics Programming Associate Job For MSc, MTech & PhD – Bioinformatics, Comp Biology Apply at AcrannoLife Genomics. MSc, MTech & PhD Bioinformatics, Computational Biology job openings at AcrannoLife Genomics. Interested and eligible applicants can check out all of the details on the same below

Senior Bioinformaticians / Bioinformatics Programming Associate

No of opening: 2

Location: Chennai

Key Skills required

• Must be proficient in Python, R studio, Java and other computational biology/ Bioinformatics Programming languages.
• Must have capabilities to independently handle large genomics datasets & develop automated pipelines for the analysis.
• Should possess Excellent Communication Skills
• Should have an Goal-oriented Mindset
• Superior organizational skills
• Multitasking ability
• Good relationship management skills

Responsibilities

• Independently write custom scripts for the analysis of large genomics data derived from high-throughput techniques (NGS)
• Designs and implement bioinformatics tools/ pipeline processes in order to analyze large scale genomics datasets.
• Develop projects and work independently on a variety of bioinformatics projects.
• Independently work on in sequence and structural pipelines, data mining, and statistical modeling pipelines.
• Works in collaboration with wet-bench biologists as well as work independently to analyze the data derived from several types of projects including cancers, genetic diseases and infectious diseases having data from microarrays, high throughput Next-Generation Sequencing & Nanopore Sequencing
• Experience with Nanopore downstream sequencing data is preferable
• Reports Generation: The candidate must be well versed in English language to write technical documents.
• Cross-Coordinate with QC for method transfer activities and complete the method-transfer activities on time.
• Coordination with cross-functional teams (Wet-Lab & Computer Programmers) to provide technical & analytical support according to the project requirements.
• Should be a good team player and complete the activity on time within project timelines.

Experience Required: Minimum 3+ years experience in handling automation for large genomic datasets (NGS)

Education Qualification: Mandatorily MSc/MTech in Bioinformatics / Computational Biology. PhD in Bioinformatics / Computational Biology can be an added advantage. However, the PhDs must mandatorily have their Masters in Bioinformatics/Computational Biology only.

How to Apply: Do Email your Resumes to: [email protected].

Here are five possible interview questions that can be asked in the technical round for the job:

1. Can you describe your experience in handling large genomic datasets and developing automated pipelines for analysis using Python, R studio, and Java? Provide examples of projects you’ve worked on. Answer: In my previous roles, I have worked extensively with large genomic datasets derived from techniques like NGS. I have developed custom scripts and automated pipelines using Python, R studio, and Java to analyze these datasets. For instance, I created a pipeline that processed NGS data to identify genetic variations associated with certain diseases. This involved data preprocessing, variant calling, and downstream analysis using these programming languages.
2. Explain your experience with Nanopore sequencing data analysis and its significance in bioinformatics. Answer: Nanopore sequencing is a valuable technique for obtaining long reads and real-time sequence information. I’ve worked with Nanopore sequencing data to analyze genetic variations, structural variations, and even RNA sequencing. It allows for studying complex genomes and transcriptomes with fewer limitations compared to traditional short-read sequencing. For example, I developed a pipeline to analyze transcript isoforms using Nanopore sequencing data, enhancing our understanding of gene expression diversity.
3. Could you discuss a challenging project where you collaborated with wet-bench biologists to analyze data from high-throughput techniques? How did you ensure effective communication and a successful outcome? Answer: In a recent project, I collaborated with wet-bench biologists to analyze RNA-seq data from cancer samples. Clear communication was vital. I participated in project meetings to understand the biological context and their experimental design. I then developed a bioinformatics pipeline to process the raw data, identify differentially expressed genes, and perform pathway analysis. Regular updates and feedback ensured that our analyses aligned with their hypotheses, leading to valuable insights into cancer-related gene expression changes.
4. Can you provide an example of a situation where you had to troubleshoot and optimize a bioinformatics pipeline for processing genomic data? How did you approach the problem-solving process? Answer: In a project involving transcriptome analysis, I encountered challenges with inconsistent read mapping rates. To address this, I first reviewed the pipeline steps to identify potential bottlenecks. I optimized parameters, incorporated quality control steps, and parallelized tasks to improve efficiency. I also introduced error handling mechanisms to ensure the pipeline’s robustness. Regularly monitoring intermediate results helped track progress and identify any deviations, ensuring the pipeline’s reliability.
5. In a fast-paced work environment, how do you manage multitasking and prioritize tasks when working on multiple bioinformatics projects simultaneously? Answer: Managing multiple projects requires effective time management and task prioritization. I start by evaluating project timelines and deadlines. Then, I break down tasks into smaller components and allocate time slots for each. I also maintain a detailed project tracker to monitor progress and track any pending tasks. Regularly reassessing priorities and being open to adjustments based on changing requirements helps ensure that all projects progress smoothly and meet their objectives.

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