Computational translational systems biology post-doctoral trainee

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