Research Associate

Job Description:

• Hands-on experience of 2-3 years in the area of genomics and bioinformatics.
• Ability to innovate and deploy problem solving skills.
• Ability to work collaboratively within a multi-disciplinary team.

Competencies and Skills:

• Data Analysis and Interpretation: Sequence Analysis: Analyze DNA, RNA, and protein sequences to identify genes, regulatory elements, and functional motifs.
• Genomic Data Interpretation: Process and interpret large-scale genomic data, such as data from next-generation sequencing (NGS) like PacBio, Nanopore, Illumina, Sanger, to uncover insights into genetic variation (SNPs and Indels), gene expression, and evolutionary relationships.
• Data Integration: Integrate diverse types of biological data (e.g., genomic, transcriptomic, proteomic) to provide a comprehensive understanding of biological processes. Develop visualization tools to help researchers understand complex datasets, such as genome browsers heatmaps, and network diagrams.
• Pipeline Development: Develop and optimize data analysis pipelines to automate repetitive tasks and ensure reproducibility.
• Innovative thinking accompanied by excellent problem solving skills.
• Work in inter-disciplinary team to advance projects, including data analysis and reporting.
• Good knowledge of English (spoken and written)

Education and Experience:

• B.Sc./B.Tech, M.Sc/M.Tech, Ph.D with strong background in bioinformatics, computational biology, computer science, or a related field.
• Basic knowledge in programming languages commonly used in bioinformatics, such as Python, R, Perl, etc.
• Experience with Bioinformatics Tools: Familiarity with popular bioinformatics tools and platforms, such as DNA and RNA assembler (DNASTAR, Unipro UGENE, Galaxy), molecular cloning tool (SnapGene, Geneious), DNA sequence aligner (Bioedit, CodonCode Aligner, CLC workbench, etc), and online tools.
• Experience with Online Databases: Familiarity with popular databases such as NCBI, DDBJ, EMBL, UniProt, RCSB PDB, and preferentially KEGG, Solgenomics, Gramene, MaizeGDB, Oryzabase, RAP-DB, Rice Genome Annotation Project, Rice Genome Hub, CottonGen,
• CottonFGD, CottonGVD, Ensembl plants, etc.
• Must have hands-on experience of handling software's used in molecular biology research