Institution/Company:

Beth Israel Deaconess Medical Center/Harvard Medical School

Location:

Boston

, Massachusetts

 United States

Job Type:

Postdoctoral

Degree Level Required:

PhD

61 days ago Apply now

Description:

  • Integrating Omics datatypes to build actionable models.
  • Developing miRNA diagnostics using miRNA profiling from concordant peripheral and brain tissue profiles of highly phenotyped subjects using miRNA profiles from serum of phenotype subjects.

Project leverages:

  • Whole genome sequencing of large cohorts of Alzheimer’s subjects.
  • 4000+ subjects
  • Resilience against AD pathology is a focus
  • 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
  • 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}
  • using reference signatures for AD facets and predicting and testing interventions that perturb or enhance AD events

Responsibilities:

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.

Qualifications:

  • 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

Additional Information:

How to Apply

provide full cv and names of 3 referees state [bioinformatics.ca] in title of email

 

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.

Keywords:

Algorithms

Analysis

Biostatistics

Biomedical

Computational

Epigenetic

Genomics

Machine Learning

Models

NGS

Ontologies

Pathway

Phenotyping

Programming

RNA

Research

Single-cell

Statistical

Tools

Posted on: