Job Description

Bioinformatics
Systems biology
Computational biology
Translational medicine
Alzheimer's disease

About us

You will be working on a project from our range of translational applications and method development opportunities using single cell RNA-Seq and spatial transcriptomics technologies. You will have access to serum, tissue spatial and single cell samples processed here at our facility.
We work on integrating:
• 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 resilience
• Modelling 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
• Spatial transcriptomics, single cell nuclear RNAseq, miRNA and whole RNA assays of ‘extreme phenotype’ centenarian subjects who show resistance or resilience to AD
• 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
• Developing miRNA diagnostics using miRNA profiling from concordant peripheral and brain tissue profiles of highly phenotyped subjects

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. 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”.

Role
The postdoctoral trainee will apprehend and curate Alzheimer’s disease datasets from our collaborators and the public domain to evaluate and synthesize molecular signatures and so integrate models that pertain to concepts of disease and resilience. Datatypes will include but are not restricted to, mRNAs, miRNAs, ncRNAs, single-cell and tissue-level transcriptomes, methylation, acetylation and genome variant data. Integrated molecular signatures from human subject data, and from model 3D cell systems data, will be assessed and incorporated into pathway-disease-drug network models. A major role will be to predict, test, and provide prioritized intervention strategies, such as drugs, miRNAs and potential diagnostics.

Datatypes will include but are not restricted to, mRNAs, miRNAs, ncRNAs, single-cell and tissue-level transcriptomes, spatial technologies, methylation, acetylation and genome variant data. Integrated molecular signatures from human subject data, will be assessed and incorporated into pathway-disease-drug network models. The project is expected to expose several layers of pathological pathway cascades, and these will need to be evaluated and modeled. A major role will be to predict, test, and provide prioritized intervention strategies, such as drugs, miRNAs and potential diagnostics.

• PhD in a quantitative field related to bioinformatics (e.g. with a specialization in bioinformatics related to genetics, neurosciences, disease modeling, pathway modeling)
• Extensive experience working with multi-omic datasets
• Ability to generate computational disease models and hypotheses
• Superb communication skills
• Ability to work independently and as part of a team
• Ability to drive a research project from design stages to data analysis, figure preparation and manuscript writing
• A passion for scientific research
• Strong organization and time-management skills
• Meticulous attention to detail
• Excellent working knowledge of R and other scripting languages

This position is a fundamentally important one and we are seeking a highly motivated individual who relishes a challenge and is not shy about diving into complex datasets.

Additional expertise
• Sound knowledge of statistics
• Experience with manipulating and curating Alzheimer’s transcriptome datasets
• Experience using large-scale datasets to rank gene and pathway candidates, and to define key network events that may be driving a disease process
• Extremely comfortable with network-orientated bioinformatics
• Knowledge of the aging and neurodegeneration research field
• A strong understanding of genetics
• Experience with human-derived model systems

Find out more about our lab at hidelab.net
As a member of Hide Lab you will:
• Work on cutting-edge research in computational and systems biology with access to 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.