Postdoctoral Position in Computational Neuroscience
Posted 24 Oct 2019
Harvard Medical School and Brigham & Women’s Hospital
To apply, please submit (1) a biosketch, (2) a cover letter outlining research interests and goals, and (3) contact information for three references to Dr. Clemens Scherzer at firstname.lastname@example.org with a cc to Marilyn Sullivan at email@example.com.
The Neurogenomics Laboratory and Center for Advanced Parkinson Research, both led by Clemens Scherzer at Harvard Medical School and Brigham & Women’s Hospital are decode causes and develop new therapies for neurodegenerative diseases such as Parkinson's and Alzheimer's disease using large-scale single-cell RNA sequencing of human brain cells, whole-genome transcriptome, metabolome analyses of large patient cohorts, combined with Electronic Health Records, systems biology, and machine learning.
The laboratory combines a strong computational neuroscience group (including computer scientists, engineers, and a statistician) with bench scientists and a clinical research group. This interdisciplinary expertise allows new, surprising discoveries and development of new methods using computational and systems biology, that then are experimentally tested using molecular biology and evaluated in real-world patients using biobank samples and longitudinal cohorts. Lab members are particularly interested in using single-cell RNA sequencing and sequencing of noncoding RNAs to understand how GWAS variants cause specific brain cells to die, and are working on prediction and prevention of disease progression in patients and on repurposing of drugs for Parkinson's patients using genome sequencing, multimodal, multiscale omics, big health data, and machine learning.
- One prior original article as first author;
- A Ph. D. or equivalent doctoral degree (preferably in bioinformatics, computer science, or statistical genetics);
- Research experience in bioinformatics and analyses of genome-wide data (for example, single cell RNA sequencing, whole genome sequencing, GWAS, eQTL, AI methods, RNA-sequencing);
- Strong quantitative skills, preferably in computer science, bioinformatics, or statistics are necessary;
- Programming background is necessary (e.g. R);
- Excellent written and spoken English.
Candidates dedicated to succeeding in an academic research career are preferred and such career paths are available.