Seeking the next leaders in computational systems medicine – Alzheimer’s Disease

Alzheimer’s resilience and pathogenesis

A postdoctoral traineeship is offered in Alzheimer’s resilience and pathogenesis.  The candidate will lead integrative study to devise and apply computational methods that expose molecular events relating to protection against cognitive loss in Alzheimer’s subjects. The study will exploit single-cell, spatial, and tissue level transcriptomic data coupled with genomic regulatory circuitry and in-depth noncoding RNA data. 

We actively encourage diversity: members of under represented minorities are particularly encouraged to apply.

The traineeship is part of our career development program to rapidly develop molecular models from signatures of resilience to apply to drug repurposing.

We will explore powerful neurodegeneration organoid assays of Alzheimer’s models where we can closely monitor pathway activity produced by Alzheimer’s pathology (see our NIH R01). The models will be compared to ongoing collected and existing human post-mortem sample data.

Developing integrative models, the candidate will elucidate the mechanism of action of and prioritize drug combinations for therapeutic intervention.

This exciting opportunity requires a candidate who is well versed in computational techniques with broad and deep experience in systems approaches to translational bioinformatics.

Alzheimer’s datasets

The candidate will apprehend and curate Alzheimer’s disease datasets to synthesize molecular signatures and build integrative models of disease and resilience. mRNAs, miRNAs, long ncRNAs, single-cell and tissue-level transcriptomes, methylation, acetylation and genome variant data will be available. Models will be incorporated into our pathway-disease-drug network. A major role will be to predict, test, and provide prioritized intervention strategies, such as drugs, miRNAs and potential diagnostics.

Required Qualifications

  • A Ph.D. in a quantitative/computational field, including, but not limited to: bioinformatics, biostatistics, genetics, computational biology, or computer science.  
  • Strong background in biostatistics and computational biology, particularly in the areas related to next generation sequencing, biological networks, and pathway analysis.  
  • Solid knowledge and background in analysis and integration of genomic data. RNA-Seq, Small RNA-Seq, single-cell RNA-seq are of particular interest. Experience with genomic data of the human brain, mouse models, or 3D models is a big plus.  
  • Strong scripting/programming skills in R and/or Python. Experience with bash scripting, and high-performance computing is a plus.  
  • Strong interest in translational science and real-world therapeutics/diagnostics applications. 
  • Strong verbal and written communication skills, evidenced by peer-reviewed publications. 
  • Background and prior work in any of the following is a strong plus: neurodegenerative diseases, neuroscience, and drug-repurposing. 
  • Solid Communication skills,
  • Ability to work independently and as part of a team.
  • Ability to drive a research project from design stages to data analysis.  

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.  

The position is available immediately and can be renewed annually

How to 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