Job Description

The Center for Genomics of Neurodegenerative Disease at the New York Genome Center seek a dynamic, self-motivated, team-oriented Staff Scientist to expand efforts in understanding mechanisms of neurodegenerative disease. We are interested in developing integrative multi-modal data analysis tools incorporating single cell and spatially resolved omics data, imaging data, clinical phenotypes, variants, and genotypes. The successful candidate will have the unique opportunity to work at the intersection of mathematical modeling, omics data analysis, workflow optimization, and resource building. 

Responsibilities may include:

Develop and optimize of complex molecular and biochemical protocols for the generation of diverse genome-wide datasets from cell lines and tissues

Facilitate the planning and co-ordination of research programs involving diverse disease cohorts in neurodegeneration

Supervise technical support staff in end-to-end NGS library preparation and quality control

Train technical support staff in the execution of project-relevant tasks and protocols

Stay up to date with advances and novel methods in biotechnology, sequencing technologies and bioinformatics tools to identify relevant developments and facilitate their on-boarding into current operations

Develop new computational, machine learning, and statistical analysis methods for integrating and analyzing large-scale, spatially resolved RNA-seq and genotypic data using current state of the art technologies

Develop a resource for the community that gives access to collected data

Work closely with experimental colleagues and cores to understand the nature of generated data

Coordinate efforts across multiple organizations (Columbia University and New York Genome Center)

Actively participate in the preparation of manuscripts for publication and present at scientific conferences

Assist in peer- and student-mentorship; and

Share expertise and provide training and guidance to group members as needed.

Position Requirements:

A minimum of a Ph.D. in computational biology, computational neuroscience, applied mathematics, computer science, or a related discipline is required

Minim of 4 years of post-Ph.D. directly relevant work experience required

In-depth conceptual or technical understanding of modern high-throughput molecular technologies in the life sciences (RNA-seq, spatial transcriptomics, immunohistochemistry) required

Prior experience with Bayesian inference, network inference, and image analysis are preferred, but exceptionally creative and driven scientists with an interest and adaptability will be seriously considered

Strong oral and written communication, data documentation, and presentation skills required

Experience writing scientific articles for publication required

Ability to handle multiple projects at the same time required

Excellent collaborative and interpersonal skills, and willingness to work in a fast-paced team environment required.

Competencies:

Technical and Professional Skills: Consistently demonstrates skills and knowledge relevant for current role; strives to expand the depth and breadth of technical and professional skills; works with a high level of integrity; exhibits focus and discipline; appropriately prioritizes, manages expectations, and delivers on commitments.

Collaborative & Communicative: Models collaboration and teamwork; brings out the best in others; effectively works with all levels, internally and externally; respects and embraces diversity of perspective; communicates clearly and listens carefully; uses good judgment as to what to communicate and when to do so.

Adaptable & Innovative: Adaptable and embraces change; develops new insights and pursues improvements and efficiency; fosters exchange of new ideas and willing to challenge the status quo; takes initiative and is solution-oriented; engages in work with passion and curiosity.