Seeking the next leaders in systems medicine – from COVID-19 to Alzheimer’s

Alzheimer’s resilience and pathogenesis

A postdoctoral traineeship is offered in Alzheimer’s resilience and pathogenesis. Our powerful computational systems medicine platform will be available to leverage pathway networks that capture the mechanisms of disease. The platform has a growing track record for the correct prediction of powerful drugs that have been effective against conditions from sepsis to neurodegeneration. With the goal of understanding the spatial-temporal relationships of pathways activated in disease, we employ a pathway-disease-drug-network to reveal the relationships of key pathway signatures to drug responses.

Editorial review of our paper using pathway networks to discover resilience drugs against sepsis

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

Projects available

We will explore up to two independent systems: (a) COVID-19 using spatial transcriptomics of in-house post-mortem infected samples from multi-tissue and single-cell assays (b) powerful neurodegeneration organoid assays of Alzheimer’s models where we can closely monitor pathway activity produced by Alzheimer’s pathology.. (see our NIH R01)

Developing signatures from these diseases, the candidate will employ our in-house network of drug-disease-pathway relationships to build in silico models. We will elucidate the mechanism of action 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.


You will apprehend and curate COVID-19 related datasets from our in-depth spatial transcriptomics assays of infected tissues of post-mortem subjects that have tested positive for SARS-CoV- 2, and relevant publicly available datasets. You will synthesize molecular signatures and so integrate models that pertain to concepts of disease. Datatypes will include but are not restricted to, mRNAs, miRNAs, ncRNAs, single-cell and tissue-level transcriptomes that have been spatially defined and assayed methylation, acetylation and genome variant data. Models will be incorporated into the pathway-disease-drug network. The project is expected to expose several layers of pathological pathway cascades, and these will need to be interpreted. A major role will be to predict, test, and provide prioritized intervention strategies, such as drugs, miRNAs and potential diagnostics.


You will apprehend and curate Alzheimer’s disease datasets to synthesize molecular signatures and build integrative models of disease and resilience. mRNAs, miRNAs, 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

  • PhD in a quantitative field related to bioinformatics (e.g. with a specialization in bioinformatics related to genetics, neurosciences, disease modelling, pathway modelling)
  • 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 language

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 ageing and neurodegeneration research field
  • A strong understanding of genetics
  • Experience with human-derived model systems

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