Postdoctoral Fellow-MSH
12 hours ago
Roles & Responsibilities:
We are inviting applications for a Postdoctoral Research Fellowship position in large scale data science, biostatistics, and multi-omics modeling with a specific interest in complex human diseases. This work will have a particular focus on the host response to SARS-CoV-2 infection with the newly founded Mount Sinai Clinical Intelligence Center. This post-doc will have the opportunity to work not only within our hospital network but within several large consortia, with access to millions of patient electronic medical record data, large-scale whole-genome and exome-scale data on patients linked to medical record data, and deeply molecularly profiled patient and control populations specific to the diseases of interest.
Background: This position will be in the labs of Dr. Noam Beckmann housed in the Departments of Medicine in the Icahn School of Medicine at Mount Sinai in Manhattan, New York, NY, USA.
The main focus of this work will be to design and perform robust, large-scale analyses of multi-omics and clinical data generated on populations of individuals to identify key regulatory components and mechanisms of complex biological processes and associated diseases and conditions, through advanced modeling of human diseases and wellness. Our labs have a large network of collaborations with both clinical and data generation groups working on these diseases as well as patient cohorts. We also have access to large datasets spanning many omics dimensions (i.e. genetic, transcriptomic [bulk and single-cell], epigenomic, proteomic and metabolomic data) with some of these having longitudinal components.
Data and Resources
The candidate will have the opportunity to work with multi-scale data and large computational resources. Among these, access to AMP-AD and psychEncode datasets as well as to institutional high-performance computing cluster and lab servers.
The postdoctoral fellow will join a dynamic team of data scientists, computer scientists, geneticists, and clinicians and participate in unique opportunities to perform large multi-scale modeling of brain diseases to derive novel biological insights.
Requirements:
The ideal candidates will have the following background:
1.PhD, MD, or MD/PhD in a quantitative science or related field (e.g., statistical genetics, computational genomics, biostatistics, systems biology, mathematics, physics, computer science, etc.)
2.Statistics or systems biology training. Should have an interest in common biostatistical and machine learning frameworks such as predictive modeling, linear modeling, network modeling, and construction of robust classifiers of disease, disease conditions, resilience, and other clinical and molecular characteristics of interest.
3.Expertise with programming and statistical software experience in R and/or Python. Additional programming languages are a plus.
4.Strong publication track record.
5.Strong communication and presentation skills with fluency in spoken and written English.
6.Prior research experience with large scale omics analyses is a plus.
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Qualifications.
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