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Computational Biologist (Machine Learning) - Center for Disease Neurogenomics

The Mount Sinai Health System
New York City, New York, US
Closing date
Dec 3, 2022

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Academic / Research
Informatics / GIS
Salary Type
Employment Type
Full time
**_Strength Through Diversity_**

**_Groundbreaking science. Advancing medicine. Healing made personal._**

**_Roles & Responsibilities:_**

The Center for Disease Neurogenomics at Icahn School of Medicine at Mount Sinai is seeking a highly motivated Computational Biologist to work in the field of Machine Learning. 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 candidate is expected to apply existing machine learning methods and develop new methods and software tools for the multi-scale single-cell transcriptome and epigenome analysis.

The successful candidate will work in a small focus group interested in developing ML algorithms to understand the genetic architecture and etiopathogenesis of Alzheimer's disease, through the lens of multi-scale single-cell profiles of brain transcriptome and regulome affected with Alzheimer's disease. The candidate is expected to develop new computational methods for the multi-scale modeling of single-cell transcriptome and regulome as well as apply state-of-the-art computational tools to omics data analysis and integration. Depending on the candidate's interests and backgrounds, specific projects may include but are not limited to studies of human brain immune cells on AD biology, neuropsychiatric disorders, deep manifold learning of disease progression, large-scale integration of multi-omic single-cell profiles, and any other open questions in single-cell brain omics.

This position has the opportunity on developing or enhancing skills in machine learning, single-cell genomics, and big data analytics. The appointed researcher will be embedded in an interdisciplinary team of clinicians, wet lab scientists, bioinformaticians, statistical geneticists, and computational biologists. We will provide you with an engaging, flexible research environment to advance your career: freedom to pursue your interests, interaction across disciplines, and a competitive salary.

The candidate should also have a strong background and experience in machine learning as well as one or more of the following areas: single-cell genomics, multi-variable statistics, open-source software development, or bioinformatics; strong programming skills using Python or R; effective communication skills; self-motivated and independent.

Roles & Responsibilities:

+ Development of new machine learning methods to aid research in understanding the genetic architecture and etiopathogenesis of Alzheimer's disease.

+ Perform rigorous and reproducible integrative analysis of large-scale single-cell genomic, transcriptomic, epigenetic, proteomic, and other omics data in healthy and disease states.

+ Critically evaluate state-of-the-art machine learning tools for omics data analysis and integration

+ Develop and maintain single-cell methods and software tools

+ Annotate and interpret human genome data using genetic/genomic/biological databases

+ Publish and present novel research findings in academic journals and conferences.

+ Participate in the preparation of manuscripts, grants, and presentations.


+ Ph.D. in Computational Biology, Bioinformatics, Computer Science, Statistics, Mathematics, Biology, Biomedical Engineering, Computer Engineering, Genetics, Biophysics, Biochemistry, Immunology, or related fields

+ At a minimum, 2 years of experience in machine learning or related data science

+ Previous experience in single-cell genomics, multi-variable statistics, or bioinformatics is preferred

+ Outstanding programming skills in at least two of these languages on a Linux environment: Python, R, Perl, Java, and C++ A strong track record of software code version control (i.e., GitHub), or contribution to open-source software development is a plus

+ Demonstrated experience designing computational methods and tools, including prior experience with algorithms relevant to computational biology, and skill and experience with statistical analysis

+ Experience working in high-performance computing (HPC) environment

+ Track record of delivering complex scientific projects through high-impact factor publications

+ Excellent communication and organizational skills with the ability to work to tight timelines, both independently and as part of a multi-disciplinary team

**_Strength Through Diversity_**

The Mount Sinai Health System believes that diversity is a driver for excellence. We share a common devotion to delivering exceptional patient care. Yet we're as diverse as the city we call home- culturally, ethically, in outlook and lifestyle. When you join us, you become a part of Mount Sinai's unrivaled record of achievement, education and advancement as we revolutionize medicine together.

We work hard to acquire and retain the best people, and to create a welcoming, nurturing work environment where you can develop professionally. We share the belief that all employees, regardless of job title or expertise, can make an impact on quality patient care.

Explore more about this opportunity and how you can help us write a new chapter in our story!

**_Who We Are_**

**Over 38,000 employees strong, the mission of the Mount Sinai Health System is to provide compassionate patient care with seamless coordination and to advance medicine through unrivaled education, research, and outreach in the many diverse communities we serve.**

**Formed in September 2013, The Mount Sinai Health System combines the excellence of the Icahn School of Medicine at Mount Sinai with seven premier hospital campuses, including Mount Sinai Beth Israel, Mount Sinai Beth Israel Brooklyn, The Mount Sinai Hospital, Mount Sinai Queens, Mount Sinai West (formerly Mount Sinai Roosevelt), Mount Sinai St. Luke's, and New York Eye and Ear Infirmary of Mount Sinai.**

_The Mount Sinai Health System is an equal opportunity employer. We promote recognition and respect for individual and cultural differences, and we work to make our employees feel valued and appreciated, whatever their race, gender, background, or sexual orientation._

**EOE Minorities/Women/Disabled/Veterans**

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