Bioinformatics and data structure lead
You will drive the lab’s computational strategy and data ecosystem. You will establish lab-wide data standards, ensure reproducibility, and develop integrative analytic frameworks that support high-impact research, grant submissions, and translational discovery. You 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. You will deploy a laboratory-wide data and work infrastructure. You 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
Key Responsibilities:
- 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 & Competencies:
- Required Education: Master’s degree in Computational Biology, Bioinformatics, Computer Science, Biostatistics, or a related field. A PhD is preferred.
- Required Experience: 3–5 years of hands-on experience in computational biology, with demonstrated contributions to genomic or transcriptomic data analysis projects.
- Technical Skills: 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).
- Leadership & Teamwork: 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.
- Independence & Problem Solving: 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.
We look for diversity.
Make an application at https://tinyurl.com/8x7h8ra7
Postdoctoral: Become a leader in data driven disease discovery
Computational Systems Medicine
Harvard Medical School and Beth Israel Deaconess Medical Center (BIDMC)
The Hide Laboratory, part of Harvard Medical School and Beth Israel Deaconess Medical Center, pioneers computational approaches to understanding the key genetic and functional ensembles that drive complex disease. Utilizing state-of-the-art genomic technologies, our focus is on studying the molecular mechanisms that humans use to resist neurodegenerative disorders or cancers with the aim of uncovering actionable diagnostic and therapeutic strategies.
Several postdoctoral traineeships are available. Apply now!
Developing miRNA diagnostics: The candidate will work with original and public transcriptomic data to develop new diagnostic discoveries for AD. The data includes miRNA profiling from concordant peripheral and brain tissue profiles of highly phenoptyped subjects. A pivotal component of this research is to investigate the role of microRNA (miRNA) in regulating AD's key signatures, particularly in relation to the disease's initiation, progression, and resilience. By leveraging systems biology frameworks, the project seeks to integrate molecular aspects of AD.
Spatial transcriptomics of AD in extreme-age brains: The candidate will access an extremely rare cohort of subjects and will study spatial and single cell transcriptomics of brain changes using cutting-edge technologies, including but not limited to single nucleus, miRNA and whole RNA assays of ‘extreme phenotype’ centenarian subjects who show resistance or resilience to AD
Computational drug-discovery to mimic resilience to AD. The candidate will develop new computational approaches to predict drugs with effective impact on changing the course of Alzheimer’s disease.
Cancer immunoediting - what processes hide tumors from immune surveillance . You will identify, genes and pathways repressed during the development of tumors and metastases in genetically engineered mouse models of solid cancer that enable tumors to evade immune surveillance. this project relies upon multimodal integration of methylation, snSEq and spatial technologies.
In addition , candidates can access training in ongoing projects in the laboratory:
- Whole genome sequencing of large cohorts of Alzheimer’s subjects.4000+ subjects
- Resilience against AD pathology is a focus
- Developing and drugging signatures of AD resilienceModelling resilience to AD pathology against AD in 3D systems (R01 project)Determining single cell signatures of resilience to AD pathology with the CIRCUITS consortium
- Further developing systems-based drug repurposing for resilience active drugs
- Mapping the AD continuum using pathway activity signatures {AD GeneDex}
- Developing reference signatures for AD facets and predicting and testing drugs that perturb or enhance AD events
Qualifications
PhD in a quantitative and/or a computational field related to bioinformatics (e.g. computer science, computational biology, biostatistics)
Proficiency working with transcriptomics datasets and assays, including RNA-Seq, scRNA-Seq, or spatially resolved transcriptomics.
Excellent programming and scripting skill in R, python, C++, or other languages. Having published/released bioinformatics packages and workflows is a big plus.
Experience with network modeling and pathway analysis is a big plus.
Ability to lead research projects evidenced by peer-reviewed publications
Experience with transcriptomics of neurodegenerative diseases, especially Alzheimer’s, is a big plus.
Located in the longwood area in Boston, the Hide Lab provides access to cutting-edge technologies at the RNA Precision Medicine Core and at the newly established Spatial Technologies Unit at BIDMC. The Hide Lab is part of the Harvard Initiative for RNA Medicine and collaborates with other several other leading research groups locally and internationally.
The Hide Lab values team-work and a healthy work-life balance. We are an equal opportunity employer and historically under-represented applicants are particularly encouraged to apply. We celebrate diversity. To learn more regarding this position or to apply please send an email to Dr. Hide (whide [at] bidmc [dot] Harvard [dot] edu) with the subject line “postdoctoral position in computational biology”.
Term
The positions are available immediately and can be renewed annually
Apply!
Email applications including curriculum vitae, a summary statement of personal objectives and research interests, PDFs of your best two papers, and the names and email addresses of three references directly to: whide [at] bidmc [dot] harvard [dot] edu
About the Hide Lab:
The Hide lab is based in Beth Israel Deaconess Medical Center/Harvard Medical School and is part of the Harvard Initiative for RNA Medicine and BIDMC Cancer Center. Our projects are funded by NIH, Harvard Medical School, and the Cure Alzheimer’s fund. We are a part of CIRCUITS consortium within CureAD foundation. Our collaboration extends to several US institutions –such as HMS, Mass General Hospital, and MIT—and international institutions.
As a member of Hide Lab you will:
Work on cutting-edge research in computational and systems biology with access to cutting-edge Alzheimer’s disease omics data.
Collaborate with world-class researchers in neurodegenerative diseases and non-coding RNA.
Receive comprehensive, focused, career directed hands-on training to pursue your goals in research and academia including: scientific communication, collaboration, and grant writing.
Benefit from training opportunities offered by Harvard Medical School, the Harvard Catalyst, and BIDMC.
Work in a vibrant and dynamic lab environment with supportive colleagues.