Lead Computational Biologist, Bioinformatics
Our client, a cutting-edge genomics research institute, is seeking an experienced Lead Computational Biologist to join our innovative team in
Baltimore, Maryland, US
. This senior position will lead a team of bioinformaticians and computational biologists focused on analyzing large-scale genomic and transcriptomic datasets. The Lead Computational Biologist will be responsible for developing and implementing advanced computational and statistical methods to uncover biological insights from complex data. You will play a critical role in designing data analysis pipelines, managing research projects, and collaborating with experimental biologists and clinicians to interpret results. Responsibilities include directing data processing, quality control, and downstream analysis of high-throughput sequencing data (e.g., RNA-Seq, ChIP-Seq, WGS). The ideal candidate will have a proven track record of developing novel analytical approaches and a deep understanding of statistical genetics, machine learning, and population genetics. Experience with cloud computing platforms (AWS, GCP, Azure) and proficiency in scripting languages (Python, R) and database management are essential. You will guide the team in exploring novel research avenues and contributing to high-impact publications and grant proposals. A PhD in Computational Biology, Bioinformatics, Computer Science, Statistics, or a related field, with at least 7 years of progressive experience in bioinformatics analysis and team leadership, is required. Strong communication and presentation skills are necessary to effectively convey complex findings to diverse audiences. Key Responsibilities: Lead and mentor a team of computational biologists and bioinformaticians. Develop and implement advanced bioinformatics analysis pipelines. Analyze large-scale genomic and transcriptomic datasets. Design and execute computational studies to address biological questions. Collaborate with experimental researchers to interpret results and guide future experiments. Manage research projects, including data management and resource allocation. Contribute to grant proposals and scientific publications. Stay current with cutting-edge technologies and methodologies in bioinformatics. Ensure data integrity and reproducibility of analyses. Present findings to internal teams and at external scientific meetings.