Do you want to be a next generation leader using computational skills to prevent brain diseases?
A bioinformatics postdoctoral fellow position is available immediately in the laboratory of noncoding RNA systems medicine at Harvard Medical School and Beth Israel Hospital (led by Dr. Winston Hide) to study resilience in Alzheimer’s disease (hidelab.wordpress.com).
We are finding the causes and targets for novel RNA and small molecule therapies for neurodegenerative diseases with a focus on Alzheimer’s disease. We exploit our powerful in silico discovery platforms applied to large-scale coding and noncoding RNA transcriptomics of human brains, single cell sequencing, whole genome sequencing and a growing collection of omics technologies. We apply novel systems biology approaches to integrate and interrogate these data to yield prioritised, actionable targets for interventions.
Our lab works in close collaboration with leading experts in Alzheimer’s, bioinformatics and noncoding RNA in a transformative environment. With the goal of accelerating the career of our postdoctoral scientists, we ensure that studies are multi-disciplinary, drive development of innovative technologies, are broadly applicable, and develop the strong leadership potential of each trainee.
The laboratory primarily uses computational modeling of neurodegenerative diseases prior to validating results with collaborators in vitro, and in mouse models. For a list of publications from the Hide lab see https://www.ncbi.nlm.nih.gov/myncbi/winston.hide.1/bibliography/public/. This position is funded by an NIH R01 research grant entitled “The Alzheimer’s Disease Resiliome: Pathway Analysis and Drug Discovery”(http://grantome.com/grant/NIH/R01-AG062547-01) under the direction of Dr. Winston Hide, Noncoding RNA Laboratory, Beth Israel Hospital, together with collaborators Dr. Doo Yeon Kim (https://www.mghmind.org/faculty/kim) and Dr. Rudolph Tanzi (https://www.mghmind.org/faculty/Tanzi) (Massachusetts General Hospital). Building on our work on resilience to sepsis (Joachim et al. 2018. The Relative Resistance of Children to Sepsis Mortality: From Pathways to Drug Candidates. Molecular Systems Biology 14 (5): e7998.) 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.
As a postdoctoral trainee you 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.
Your qualifications. We would like you to have:
- PhD in a quantitative field related to bioinformatics (e.g. with a specialization in bioinformatics related to genetics, neurosciences, disease modeling, pathway modeling)
- At least one publication with you as first author
- Extensive experience working with multi-omic datasets
- Ability to generate computational disease models and hypotheses
- Superb communication skills using excellent spoken and written english
- 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
- Evidence of bioinformatics and programming expertise
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.
- 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
The position is available immediately and can be renewed annually