Careers

Available Positions

Our faculty and staff at the Department of Genetics and Genomic Sciences are leading the way in biomedical science and personalized medicine. In addition to the academic and clinical support our faculty and staff receives, you’ll also receive a wide range of personal and professional benefits.

The Department of Genetics and Genomic Sciences at the Icahn School of Medicine at Mount Sinai, in New York, NY invites applications for multiple tenure-eligible or tenured faculty positions at the Assistant, Associate, or Full Professor levels.

Mount Sinai is ranked as one of the nation’s top biomedical institutions in research, patient care, and education. Since 2011, Mount Sinai has made major investments to attract world class expertise and build cutting-edge resources to fuel advanced research in biomedical data science and innovative technology development. Faculty recruits will be appointed in the Department of Genetics and Genomic Sciences (GGS), which is currently the 5th ranked genetics department nationally based on NIH funding. Based on work in GGS, Mount Sinai was recently recognized as the 4th most innovative data science organization in the world by Fast Company.

We seek exceptional faculty candidates with expertise in developing and/or applying advanced computational, molecular, cellular, or engineering strategies to advance functional genomics research. Candidates can focus on translation of these strategies to any area of medicine and/or disease. Relevant research directions include but are not limited to high-throughput functional genomics screening using genome editing and other technologies, in-situ transcriptomics/proteomics screening, single cell and/or spatial methods, functional genome annotation, genome graph representation and genome assembly. Another direction of interest is to integrate different types of biomedical data to gain insights on how the spectrum of genomic perturbations and associated transcriptomic and/or proteomic responses contribute to different biological processes or disease development. As biomedical research becomes an increasingly interdisciplinary science, success will require a goal-directed, team-oriented approach. We seek faculty members interested in working in a fast paced, highly collaborative environment in which interdisciplinary teams of data scientists, technology innovators, and experts in key diseases work together with the shared goal of leveraging large-scale data, coupled with applications of advanced multi-omics technologies, to predict, test, and translate novel therapies faster and more effectively.

Applicants should hold a Ph.D., M.D. or M.D./Ph.D. and are expected to develop independent research programs and participate in graduate student mentoring and teaching. Senior applicants are expected to have a national or international reputation in their research fields and successful track records of research funding. We offer highly competitive recruitment packages, strong institutional commitments to faculty support, comprehensive benefits, relocation services, and a rewarding work and life environment. The Icahn School of Medicine is located in the heart of Manhattan, one block from central park.

Applicants should prepare the following materials and submit the application at https://bit.ly/ggsrecruit2021w.

  1. Cover letter (please clearly state your area of research interest)
    Please name the file as: Applicant’sLastName.Applicant’sFirstName.pdf
  2. CV
    Please name the file as: Applicant’sLastName.Applicant’sFirstName.CV.pdf
  3. Research plan (3-page max without references)
    Please name the file as: Applicant’sLastName.Applicant’sFirstName.ResearchPlan.pdf

Completed applications will be reviewed on a rolling basis with an initial deadline of December 15, 2021. Review of applications will begin immediately, and will remain open until positions are filled.

The Icahn School of Medicine at Mount Sinai is an Equal Opportunity and Affirmative Action Educational Institution and Employer. Women and members of underrepresented minority groups are strongly encouraged to apply. In addition, candidates are encouraged to use the cover letter to provide any additional information the candidate feels relevant to disadvantaged backgrounds.

APPLY HERE

Please contact ggsrecruitment@mssm.edu with any questions.

The Center for Transformative Disease Modeling is seeking for highly qualified candidates for a faculty position in computational Neuroscience. The computational neuroscientist is expected to develop cutting-edge data mining and network inference algorithms to analyze large-scale genetic, epigenetic, genomic, and clinical data in neurodegenerative diseases such as Alzheimer's and Parkinson's diseases. This candidate will be responsible for delivery of novel disease biomarkers and targets, biologically plausible disease models for experimental validations.

 Qualifications:

  • PhD in Neuroscience, Computational Neuroscience or a closely related field and 3+ years of experience in these fields.
  • Up-to-date knowledge on signaling pathways and mechanisms in neurodegenerative diseases.
  • Previous experience in target identification or validation in neurodegenerative diseases, especially Alzheimer’s disease.
  • Expertise in cutting edge techniques, particularly single cell sequencing as well as modeling of brain cell communications and brain connectome.
  • Suitable for working in a collaborative multi-disciplinary environment.
  • Strong communication skills, and an ability to collaborate with peers and train postdocs & graduate students effectively are required.

Interested applicants should send Cover Letter, CV, and Research Plan to Professor Bin Zhang at bin.zhang@mssm.edu

The Center for Transformative Disease Modeling is seeking for highly qualified candidates with expertise and strong publication record in the development and/or application of system pharmacology approaches for drug discovery and development. The systems pharmacologist is expected to develop and apply systems and network biology approaches to select druggable targets for diseases like Alzheimer's disease, identify drug candidates, study drug activities (binding and specificity) and generate/optimize drug lead molecules. The candidate will be responsible for developing drug-disease network models and evaluating drug candidates based on ADME-T properties, pharmacological data and therapeutic efficacy. The candidate will collaborate with pre-clinical and clinical teams to ensure transfer of quantitative knowledge to support the design of experimental validations and early clinical studies. 

Qualifications

  • PhD in Pharmacology, Chemistry, Chemical Engineering, Bioinformatics, Computational/Systems Biology, or a related field and a 3+ years of experience in these fields.
  • Proficient in mechanistic modeling using R, Matlab, python or any equivalent software packages is required. Advanced knowledge of AI-based tools to efficiently analyze large datasets is desired.
  • Demonstrated expertise in computational approaches for drug design (e.g. ligand-based and structure-based drug design), especially in the area of quantitative systems pharmacology is required. Expertise with statistics is highly desirable.
  • Proven track records of applying system biology / network methods to issue resolution in drug discovery and developmental challenges and aiding in model-based drug development are required.
  • Expertise in neurodegenerative disease or cancer is also appreciated.
  • Strong communication skills, and an ability to collaborate with peers and train postdocs & graduate students effectively are required.

Interested applicants should send Cover Letter, CV, and Research Plan to Professor Bin Zhang at bin.zhang@mssm.edu

The Bunyavanich Lab is seeking talented individuals who can fulfill the responsibilities and requirements below to apply for post-doctoral positions in our lab.  Our interdisciplinary team led by Professor Supinda Bunyavanich applies epidemiology, multi-omics, and systems biology to interpret multi-scale data generated from human cohorts with asthma and allergic diseases.

Responsibilities:

  • Analyze high-throughput sequence data.
  • Develop and implement methods to analyze these data.
  • Maintain large datasets linked to clinical data.
  • Communicate progress with PI regularly and contribute to the success of the research team.
  • Develop and maintain productive collaborations within Mount Sinai and with outside researchers in academia and industry.
  • Publish and present novel research findings in academic journals and conferences
  • Some supervision of trainees and technical staff may also be required.

Requirements:

  • Degree in bioinformatics, computer science, computational biology, genomics, or a related field.
  • Outstanding programming skills in R, Python, and Unix shell scripting.
  • Excellent track record of analyzing sequence data. Experience with clinical cohorts and microbiome analysis a plus.
  • Demonstrated knowledge of statistics and statistical genetics. Familiarity with genomic data tools, repositories, and databases.
  • Strong attention to detail and solid analytical skills.
  • Ability to work hard and independently while contributing to the team effort and adhering to deadlines.
  • Excellent oral and written communication skills with track record of productive collaborations.
  • Demonstrated ability to work concurrently on several projects, and good understanding of analytic complexities to do independent research as well as assist other researchers.

Interested and qualified candidates may inquire about positions by submitting a CV and detailed letter of interest to Professor Supinda Bunyavanich (Supinda.Bunyavanich@mssm.edu).

The Fang Lab has rich experience in long read sequencing technology (both PacBio and Oxford Nanopore), systems biology and precision medicine. We use long read sequencing to make new discoveries from the human genome, epigenome and transcriptome (Genome Research, 2018; Nature Genetics, 2019). We also pioneered the fast-growing field of bacterial epigenomics (Nature Biotechnology, 2012; Nature Reviews Genetics, 2018, Nature Microbiology, 2020), and the use of DNA methylation for high resolution microbiome analysis (Nature Biotechnology, 2018; Nature Methods, 2021).

Opening

We are looking for highly motivated PostDoc Fellows to (1) develop innovative epigenomics and transcriptomics technology using long read sequencing; (2) discover novel insights in human diseases; (3) translate basic science discoveries into medical impact.

Successful candidates will have unique opportunities with:

(i) a highly interdisciplinary and innovative lab culture where members with dry/wet background closely discuss and learn from each other;

(ii) our unique expertise in long read sequencing, multi-omics, rich clinical samples and strong collaborators; 

(iii) take the lead role in projects developing cutting edge, pioneering technologies with high biomedical and clinical impact; 

(iv) strong mentorship in both research and career development; 

(v) Compensations are highly competitive with subsidized housing in New York City.

Requirements

  1. Candidates with computational and/or experimental background are both welcome.
  2. Ability to learn and master new knowledge and technologies,
  3. Abilities to lead an independent research direction while adapting to a collaborative environment,
  4. An innovative yet critical thinker.

How to apply

Please send the following to fanggang@gmail.com: 1) A brief cover letter, 2) CV with a list of publications, 3) PDF files for the papers in which you are first/co-first author.