Our client, a leading biopharmaceutical company at the forefront of precision medicine, is seeking an exceptional Senior Computational Biologist to join their innovative genomics team. This is a fully remote position, offering the opportunity to contribute to groundbreaking research from anywhere in the US. You will be responsible for the analysis of large-scale genomic and transcriptomic datasets to identify novel therapeutic targets, understand disease mechanisms, and discover biomarkers for drug development. This role requires a deep expertise in bioinformatics, statistical genetics, and machine learning applied to biological data. You will work closely with experimental biologists, data scientists, and clinicians to interpret complex biological questions and design data-driven research strategies. The ideal candidate possesses a strong quantitative background, a proven track record of publishing in high-impact journals, and extensive experience with next-generation sequencing (NGS) data analysis pipelines. Proficiency in programming languages such as Python or R, along with experience in statistical modeling, machine learning algorithms, and database management, is essential. You should be adept at visualizing and communicating complex genomic findings to both technical and non-technical audiences. The ability to work independently, manage multiple research projects concurrently, and collaborate effectively within a distributed team is crucial for success in this remote role.

Key Responsibilities

Analyze large-scale genomic, transcriptomic, and epigenomic datasets from various experimental platforms. Develop and implement bioinformatics pipelines for NGS data processing, quality control, and variant calling. Apply statistical and machine learning methods to identify disease-associated genetic variants, gene expression patterns, and biomarkers. Collaborate with experimental biologists to design studies, interpret results, and generate hypotheses. Build predictive models for drug response and disease progression. Contribute to the development of novel computational methods and algorithms for biological data analysis. Visualize complex genomic data and communicate findings effectively through presentations and written reports. Work closely with IT and data engineering teams to manage and optimize data storage and computational infrastructure. Stay current with the latest advancements in genomics, bioinformatics, and computational biology. Mentor junior computational biologists and contribute to the scientific growth of the team.

Qualifications

Ph.D. in Computational Biology, Bioinformatics, Statistics, Computer Science, or a related quantitative field. Minimum of 5 years of post-doctoral and/or industry experience in computational biology or bioinformatics, with a focus on genomics. Extensive experience analyzing diverse genomics data types (WGS, WES, RNA-Seq, ChIP-Seq, ATAC-Seq). Proficiency in programming languages such as Python and/or R, and associated scientific libraries. Strong understanding of statistical modeling, machine learning, and data mining techniques. Experience with cloud computing platforms (AWS, GCP, Azure) and high-performance computing (HPC) environments. Excellent communication, collaboration, and problem-solving skills. Proven ability to work independently and manage projects effectively in a remote setting. Demonstrated track record of scientific publications and presentations. This is a unique opportunity to leverage your computational expertise to accelerate drug discovery and development in a dynamic, remote-first environment. Apply To this Job