We are seeking a skilled and detail-oriented Bioinformatician to support data-driven research and development in the field of [genomics, personalized medicine, drug discovery, or agricultural biotechnology]. The successful candidate will analyze complex biological datasets using computational tools and contribute to the interpretation of biological insights that drive innovation and scientific discovery.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 genomic, transcriptomic, proteomic, and metabolomic data. Develop, implement, and optimize computational pipelines for data processing and analysis. Collaborate with biologists, data scientists, and clinicians to design experiments and interpret results. Maintain and manage biological databases, ensuring data integrity, accessibility, and reproducibility. Perform statistical analyses and machine learning to uncover patterns in biological systems. Visualize complex datasets and present findings in a clear, actionable manner. Stay up to date with the latest bioinformatics tools, databases, and methodologies. Document all computational methods, workflows, and results for reproducibility and publication. Qualifications:Masters or Ph.D. in Bioinformatics, Computational Biology, Computer Science, Genomics, or a related field. [25+] years of hands-on experience analyzing high-throughput biological data. Proficiency in programming languages such as Python, R, or Perl. Experience with bioinformatics tools (e.g., BLAST, GATK, STAR, BWA, SAMtools) and databases (e.g., Ensembl, NCBI, UniProt). Familiarity with cloud computing platforms (e.g., AWS, GCP) and workflow management tools (e.g., Snakemake, Nextflow). Strong knowledge of statistics, data visualization, and biological interpretation. Excellent communication and teamwork skills. Preferred Skills:Experience with single-cell sequencing or spatial transcriptomics. Knowledge of machine learning and AI applications in biology. Experience in clinical bioinformatics, biomarker discovery, or regulatory submissions (e.g., FDA/EMA). Familiarity with version control systems (e.g., Git) and containerization (e.g., Docker, Singularity).