A position at the Roussos Lab/Pamela Sklar Division of Psychiatric Genomics (DPG) in Icahn School of Medicine at Mount Sinai is available for Data Manager. The post will suit an ambitious and talented individual who is interested in applying his/her skills at the interface of human disease and genetics.

The appointed data manager will be embedded in an interdisciplinary team of clinicians, wet lab scientists, bioinformaticians, statistical geneticists and computational biologists. The Roussos Lab/Pamela Sklar Division of Psychiatric Genomics studies the genetic mechanisms through which risk genetic variants increase vulnerability for neuropsychiatric traits, including schizophrenia, bipolar disorder and Alzheimer’s disease. Distinguishing features of our research are the generation of large-scale omics data in human brain tissue, including epigenomics and transcriptomics and the use of genome sequencing for big data integration. Successful candidate oversees the development and use of data systems and discovers efficient ways to organize, store and analyze data with attention to security and confidentiality. The ideal candidate will have a strong understanding of databases and data analysis procedures and will possess excellent troubleshooting skills.

Responsibilities:

• Develop and maintain genetic, genomic, and biological databases to annotate and interpret human genome data.
• Create and enforce policies for effective data management.
• Formulate techniques for quality data collection to ensure adequacy, accuracy and legitimacy of data.
• Devise and implement efficient and secure procedures for data handling and analysis.
• Establish rules and procedures for data sharing with internal and external collaborators.
• Assist with reports and data extraction when needed.

Job requirements:

• BSc/BA in computer science or relevant field.
• Proven experience as data manager.
• Excellent understanding of data administration and management functions (collection, analysis, distribution etc.).
• Outstanding programming skills in at least two of these languages on a Linux environment: Python, R, bash, Perl, Java, and C++.
• Familiarity with modern database and information system technologies
• An analytical mindset with problem-solving skills
• Excellent communication and collaboration skills

A position at the Roussos Lab/Pamela Sklar Division of Psychiatric Genomics (DPG) in Icahn School of Medicine at Mount Sinai is available for a Postdoctoral Fellow in Statistical and Computational Genomics. The post will suit an ambitious and talented individual who is interested in applying his/her skills at the interface of human disease and genetics.

The appointed researcher will be embedded in an interdisciplinary team of clinicians, wet lab scientists, bioinformaticians, statistical geneticists and computational biologists. The Roussos Lab/Pamela Sklar Division of Psychiatric Genomics studies the genetic mechanisms through which risk genetic variants increase vulnerability for neuropsychiatric traits, including schizophrenia, bipolar disorder and Alzheimer’s disease. Distinguishing features of our research are the generation of large-scale omics data in human brain tissue, including epigenomics and transcriptomics and the use of genome sequencing for big data integration. As part of the Million Veteran Program, an initiative in Precision Medicine by the Department of Veteran Affairs, we are performing integrative analysis of functional omics data (transcriptomics and epigenomics) with genotypes and clinical data in one million individuals. The successful candidate will be primarily responsible for: (1) computational analyses of whole-genome/exome sequencing datasets and genome-wide SNP array, with the aim to characterize different classes of sequence and genotyping variants; (2) modeling the genetic architecture from sequencing and genome-wide SNP data with aim to compare traits across molecular pathways and functional omics data derived from multiple tissues/cell types; and (3) integrate SNP predictors of omics data with large-scale biobank datasets, such as MVP to identify molecular targets and pathways affected across multiple traits.

Responsibilities:

• Develop and maintain genetic, genomic, and biological databases to annotate and interpret human genome data.
• Analyze whole genome/exome sequencing and genome-wide SNP array data.
• Determine variables to be studied, sample size, and appropriate data collection and analysis methods.
• Develop and implement algorithms, statistical methods and software to analyze large-scale human sequencing data and perform integrative functional analysis.
• Publish and present novel research findings in academic journals and conferences.

Job requirements:

• PhD in Statistics, Biostatistics, Statistical Genetics, Genetic Epidemiology, or related discipline are required.
• Firm grounding in statistical methods for genome data analysis.
• Experience with biological datasets and next generation sequencing data.
• Experience analyzing large-scale genetic datasets in complex human traits or disease and using main statistical packages for genetic data (e.g. GCTA and SNPtest).
• Experience working with large publically available databases (eg. 1000 Genomes, UK10K, ExAC, gnomAD, HGMD, TCGA, COSMIC, etc.).
• Outstanding programming skills in at least two of these languages on a Linux environment: Python, R, bash, Perl, Java, and C++.
• Track record of delivering complex scientific projects through high impact factor publications.
• Excellent communication and organizational skills with ability to work to tight timelines, both independently and as part of a multi-disciplinary team.

A position at the Roussos Lab/Pamela Sklar Division of Psychiatric Genomics (DPG) in Icahn School of Medicine at Mount Sinai is available for a Postdoctoral Fellow in one or more of the following areas: machine learning, deep learning, computer vision/image processing, signal processing, and data analysis. The post will suit an ambitious and talented individual who is interested in applying his/her skills at the interface of human disease and genetics.

The appointed researcher will be embedded in an interdisciplinary team of clinicians, wet lab scientists, bioinformaticians, statistical geneticists and computational biologists. The Roussos Lab/Pamela Sklar Division of Psychiatric Genomics studies the genetic mechanisms through which risk genetic variants increase vulnerability for neuropsychiatric traits, including schizophrenia, bipolar disorder and Alzheimer’s disease. Distinguishing features of our research are the generation of large-scale omics data in human brain tissue, including epigenomics and transcriptomics and the use of genome sequencing for big data integration. As part of the CommonMind Consortium and PsychENCODE Project, we are generating multi-scale omics data in human brain tissue that involves multiple brain regions and cell types, clinical diagnosis and developmental stages. As part of the Million Veteran Program, an initiative in Precision Medicine by the Department of Veteran Affairs, we are performing integrative analysis of functional omics data (transcriptomics and epigenomics) with genotypes and clinical data in one million individuals. The successful candidate will be primarily responsible for integrative analysis of multi-scale omics data with genomics and clinical phenotypes from the Million Veteran Program which involves: (1) formulation of novel mathematical tasks which are achievable given the type of observational data; (2) design of models which accurately capture the complexities of the data; and (3) fast and scalable algorithms to fit the proposed models to data. The overall goal is the identification of: (1) molecular markers that are associated with specific traits; (2) disease sub-phenotypes that are driven by perturbations in molecular traits; and (3) compounds that reverse the disease-associated omics perturbations by applying drug repurposing analysis.

Responsibilities:

• Development of innovative theoretical analysis and computational methodologies for deep and/or machine learning technologies, customized to large-scale omics and biobank data.
• Collaboration with experts from various scientific disciplines and applications, and following team planning, goals and quality processes.
• Publish and present novel research findings in academic journals and conferences.

Job requirements:

• Ph.D. in computer science, electrical engineering, computer engineering or related field.
• Strong theoretical background in: constructive approximation; functional, complex, and real analysis; as well as numerical analysis and approximation of partial differential equations.
• Expertise in deep learning and reinforced learning; graphical/network models; kernel methods; sparse grid methods; compressed sensing, thresholding, and greedy approaches; stochastic optimization; as well as convex and non-convex regularizations.
• Experience with biological datasets and next generation sequencing data.
• Outstanding programming skills in at least two of these languages on a Linux environment: Python, TensorFlow / PyTorch, R, bash, Perl, Java, and C++.
• Track record of delivering complex scientific projects through high impact factor publications.
• Excellent communication and organizational skills with ability to work to tight timelines, both independently and as part of a multi-disciplinary team.

A position at the Roussos Lab/Pamela Sklar Division of Psychiatric Genomics (DPG) in Icahn School of Medicine at Mount Sinai is available for a Postdoctoral Fellow in Computational Biology and Genomics. The post will suit an ambitious and talented individual who is interested in applying his/her skills at the interface of human disease and genetics.

The appointed researcher will be embedded in an interdisciplinary team of clinicians, wet lab scientists, bioinformaticians, statistical geneticists and computational biologists. The Roussos Lab/Pamela Sklar Division of Psychiatric Genomics studies the genetic mechanisms through which risk genetic variants increase vulnerability for neuropsychiatric traits, including schizophrenia, bipolar disorder and Alzheimer’s disease. Distinguishing features of our research are the generation of large-scale omics data in human brain tissue, including epigenomics and transcriptomics and the use of genome sequencing for big data integration. As part of the CommonMind Consortium and PsychENCODE Project, we are generating multi-scale omics data in human brain tissue that involves multiple brain regions and cell types, clinical diagnosis and developmental stages. The successful candidate will be primarily responsible for: (1) computational analyses of HiC, capture-C and HiChIP omics data, with the aim to characterize and annotate the structure of the 3D Genome; (2) identify differences in the 3D genome across cell types, brain regions, neuropsychiatric diseases and developmental stages; and (3) identify association of the structure of 3D Genome with common and rare genetic variants and perform colocalization with risk variants across neuropsychiatric diseases.

Responsibilities:

• Analyze next generation sequencing data, including HiC, Capture-C and HiChIP.
• Develop and maintain genetic, genomic, and biological databases to annotate and interpret human genome data.
• Develop and implement algorithms, statistical methods and software to analyze large-scale human sequencing data and perform integrative functional analysis.
• Publish and present novel research findings in academic journals and conferences.

Job requirements:

• PhD in Computational Biology, Bioinformatics, Computer Science, Biology, Biomedical Engineering, Computer Engineering, Genetics or related field.
• Strong genomics and genetics background.
• Experience with biological datasets and next generation sequencing data, including HiC assays.
• Demonstrated experience designing computational methods and tools, including prior experience with algorithms relevant to computational biology, and skill and experience with statistical analysis.
• Outstanding programming skills in at least two of these languages on a Linux environment: Python, R, bash, Perl, Java, and C++.
• Track record of delivering complex scientific projects through high impact factor publications.
• Excellent communication and organizational skills with ability to work to tight timelines, both independently and as part of a multi-disciplinary team.