What are the responsibilities and job description for the Bioinformatician and Data Infrastructure Lead position at Beth Israel Deaconess Medical Center?
Responsibilities
About the job
The Hide Laboratory at Beth Israel Deaconess Medical Center at Harvard Medical School applies cutting-edge genomic and computational approaches to understand resilience and vulnerability in neurodegenerative disease. We seek a Bioinformatician / Data Infrastructure & Analytics Lead who will drive the lab’s computational strategy and data ecosystem. The successful candidate will establish lab-wide data standards, ensure reproducibility, and develop integrative analytic frameworks that support high-impact research, grant submissions, and translational discovery. The bioinformatician will manage and deliver developing code and pipelines for RNA-Seq, single-cell RNA-Seq, spatial transcriptomics, and proteomics profiling and also laboratory algorithm package maintenance and development. They will deploy a laboratory-wide data and work infrastructure. The successful candidate will be expected to take ownership of the lab's data infrastructure, serve as a thought partner in experimental design and interpretation, and help shape the Hide Lab’s computational capacity for long-term success in cognitive resilience and neurodegeneration research.
You will drive:
- Pipeline Development: Build, maintain, and optimize scalable, reproducible analysis workflows for RNA-seq, single-cell, spatial transcriptomics, and other genomic data types.
- Analysis & Integration: Conduct sophisticated pathway and network based reasoning, integrative bioinformatics, and advanced data visualization to translate signatures into biological insight and clinical outcomes.
- Infrastructure Building: Develop/integrate existing user-friendly platforms, databases, and interfaces that enable seamless exploration and reproducible use of lab-generated and public datasets.
- Collaboration: Partner closely with experimental and computational scientists on study design, power analysis, data interpretation, and manuscript preparation.
- Data Leadership: Design and oversee robust systems for organizing, curating, and sharing multi-omic data. Ensure all data practices are compliant with National Institutes of Health, institutional, and FAIR data standards. Ensure cross-project metadata consistency, gene list registration and provenance, reusable analytics.
- Training & Mentorship: Meticulously document all pipelines and code. Teach computational best practices and mentor trainees in reproducible data science methods.
- Strategic Role: Anticipate the lab's future computational needs and lead and operationalize activites such as application of embeddings, network models, or scalable cloud infrastructure.
Qualifications
About you
You have solid quantitative and computational skills. You have evidence of experience in genomics/transcriptomics/NexGen analysis. You have excellent communication skills, are highly independent, and relish learning new technologies and biology. You care about data structure, you have an active interest in community development of bioinformatics, and you understand the need and foundation required to develop and deploy new technology including AI.
Essential Skills
Minimum of master’s degree in Computational Biology, Bioinformatics, Computer Science, Biostatistics, or a related field. A PhD is preferred
3–5 years of hands-on experience in computational biology, with demonstrated contributions to genomic or transcriptomic data analysis projects.
Strong programming proficiency in R and/or Python and shell scripting. Experience with workflow management tools (e.g., Nextflow, Snakemake), reproducibility frameworks (e.g., Docker, Conda), and data versioning (e.g., Git).
Effective science communication
Ideal Skills
- We seek real evidence of leadership in data organization, teaching, or team-based computational support. Excellent communication skills with a proven ability to bridge computational and biological perspectives.
- Ability to work autonomously while aligning with the lab’s strategic scientific goals. Capable of developing robust, creative solutions for complex challenges in multi-omic integration and data scaling.
Find out more about the Hidelab https://research.bidmc.org/winston-hide
We look for diversity.
Make an application at https://tinyurl.com/8x7h8ra7
We are an equal Opportunity Employer and we particularly welcome applications from women, persons with disabilities, protected veterans, and members of minority groups. International applicants are welcome to apply.