A postdoctoral fellow position is available immediately in the Department of Pathology at Harvard Medical School/Beth Israel Deaconess Medical Center to study resilience in Alzheimer’s disease. The position is funded by an NIH R01 research grant entitled “The Alzheimer’s Disease Resiliome: Pathway Analysis and Drug Discovery under the direction of Dr. Winston Hide (Systems RNA medicine), Noncoding RNA Laboratory, Beth Israel Hospital, together with collaborators Dr. Doo Yeon Kim and Dr. Rudolph Tanzi (Massachusetts General Hospital). We seek to understand the manner in which some individuals appear to be resilient to the pathologies associated with the onset of Alzheimer’s disease and to use that information to promote healthy ageing and decrease the severity of neurodegenerative diseases. The laboratory primarily uses computational modeling of neurodegenerative diseases prior to validating results with collaborators in vitro, and in mouse models. list of publications from the Hide lab
Responsibilities
The postdoctoral trainee will apprehend and curate Alzheimer’s disease datasets from 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 organoid 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.
Required 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 language
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
email to whide