We are seeking a highly motivated and skilled Bioinformatics Scientist to join our team. In this role, you will lead and contribute to the design, development, and execution of bioinformatics analyses to support [genomic research, drug discovery, precision medicine, or other biological innovations]. You will work with high-throughput biological data, develop computational pipelines, and help interpret complex datasets to generate meaningful scientific insights.InfoResumeEdge is the first platform that is completely free for both recruiters and job seekers. By creating a profile, you gain global visibility, which significantly boosts your chances of instant hiringwhether for remote or onsite roles. We encourage professionals to build their profiles today and connect with top opportunities worldwide.Key Responsibilities:Analyze large-scale biological datasets, including next-generation sequencing (NGS), transcriptomics, epigenomics, and proteomics. Develop and maintain robust, scalable computational pipelines for data preprocessing, alignment, annotation, and statistical analysis. Collaborate with molecular biologists, clinicians, and data scientists to support interdisciplinary research and product development. Interpret and visualize biological data to identify patterns, biomarkers, or novel mechanisms relevant to human health and disease. Maintain accurate and well-documented code, protocols, and analysis reports to ensure reproducibility. Evaluate and integrate new bioinformatics tools, algorithms, and public datasets into research workflows. Present research findings to internal teams and contribute to scientific publications, presentations, and grant proposals. Qualifications:Ph.D. or Masters degree in Bioinformatics, Computational Biology, Genomics, or a related field. [25+] years of hands-on experience in bioinformatics or computational biology. Strong programming and scripting skills (e.g., Python, R, Bash). Experience with NGS technologies and tools (e.g., BWA, STAR, GATK, DESeq2, SAMtools, BEDTools). Familiarity with biological databases (e.g., Ensembl, NCBI, UCSC Genome Browser). Solid foundation in molecular biology, genetics, and statistics. Strong communication skills and ability to work in a collaborative, fast-paced environment. Preferred Skills:Experience with cloud computing environments (AWS, GCP) and workflow management tools (Nextflow, Snakemake). Familiarity with version control (e.g., Git) and containerization (Docker, Singularity). Background in a specific therapeutic area (e.g., oncology, rare disease, infectious disease). Experience with single-cell data analysis, multi-omics integration, or clinical genomics.