Postdoc/Bioinformatician/Computational Biologist to study human neurodegenerative diseases
We are seeking an innovative Bioinformatician who will be integral in a multidisciplinary effort for identifying markers of selective vulnerability in neurodegenerative diseases, with the goal of developing effective therapeutic strategies.
The ideal candidate has a strong background in bioinformatics, computer science or software engineering, experience in the life sciences. Working with neuropathologists, neurologists and neuroscientists, you will help design and analyze high dimensional data (e.g., single-cell sequence assays, genotype or WGS data, proteomics data, etc.) from human brain tissues, utilize bioinformatics tools and databases to provide biological interpretations and insights.
Successful candidates should be scientifically motivated self-starters, comfortable working in a highly productive academic environment, and keen on modeling biological processes using rich datasets.
This position presents an outstanding training experience for a bioinformatics scientist who wishes to break into dementia, Alzheimer’s disease, and neurodegenerative disease field. Neurodegenerative conditions, including Alzheimer’s disease and frontotemporal lobar degeneration, selectively target specific neuronal subpopulation making it imperative to define the molecular signature of these vulnerable populations for achieving effective treatment
The candidate will work with a multidisciplinary team as part of the Weill Neurohub, which brings together world-class researchers and clinicians at three premier West Coast research institutions to speed the development of new treatments for neurological and psychiatric diseases. The primary appointment will be at the Memory and Aging Center at UCSF at the Grinberg (https://grinberglab.ucsf.edu/) and Seeley (https://seeleylab.ucsf.edu/lab) Labs
• Create, implement and maintain pipelines for processing high-throughput next-generation sequencing data for genomics, epigenomics, and transcriptomics studies
• Analyze and extract biological insights from internal and public datasets by developing new computational methods or leveraging existing methods when possible
• Implement and develop data analysis/visualization tools to enable data access
· MS or Ph.D. in Bioinformatics, Computational Biology, Computer Science, Mathematics, Statistics or a related field
· Experience with pipeline development, bioinformatics tools, and data management
· Strong demonstrated competence in languages such as R or Python for bioinformatics analyses
· Experience with cloud-based storage and service tools (Google, AWS, etc.)
· Strong collaboration and communication skills are expected
· Experience with epigenetic and transcriptomic data and academic achievement are pluses
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