Postdoctoral Research Scientist
Content + Source + Freshness • 14 Dec 2025 • 95% confidence
Offer value
High value due to unique research topics, interdisciplinary collaboration, and impactful application of findings.
- Engaging in research on Alzheimer's and neurodegeneration
- Opportunities for interdisciplinary collaboration
- Competitive pay based on experience
- Ideal for candidates with computational biology expertise.
Pros
- Opportunity to engage in cutting-edge research on Alzheimer's disease.
- Collaboration with a multidisciplinary research team.
- Potential contributions to significant findings in neurodegeneration.
Cons
- High expectations for comprehensive data analysis.
- Pressure to meet research deadlines.
- Requires strong teamwork and communication skills.
Who it's for
Postdoctoral • Research-focused collaboration
Good fit
- Postdoctoral researchers in computational biology.
- Candidates passionate about neurobiology.
- Individuals aiming for impactful research roles.
Not recommended for
- Those without computational skills.
- Candidates preferring traditional biology roles.
- Individuals unwilling to work in collaborative settings.
Motivation fit
Key skills
About the job
A Postdoctoral Research Scientist position in Computational Biology is available at the Center for Translational and Computational Neuroimmunology (CTCN) in the Department of Neurology at Columbia University Irving Medical Center in New York, NY. The candidate will be co-supervised by Drs. Hans-Ulrich Klein and Philip De Jager.
We are looking for an enthusiastic and motivated individual to join our computational team. Our overarching research goal at the CTCN is to identify and model molecular mechanisms that drive neurodegeneration, with a focus on Alzheimer’s disease and related dementias (ADRD). Our team develops and applies systems biology approaches to genome-wide, high-dimensional human data generated from large, well-characterized cohorts. These data are often multi-modal (genetic, epigenetic, transcriptomic, proteomic, glycoproteomic), spanning various brain regions and peripheral tissues, and acquired at multiple resolutions (tissue-level, single-cell/nucleus, and spatial transcriptomic data), requiring complex integrative analyses. The successful candidate will lead the analysis of a large, newly generated dataset from cognitively and motor-relevant tissues (prefrontal cortex, motor cortex, spinal cord, muscle) to identify shared and distinct molecular pathways underlying cognitive and motor decline. Tissue donors underwent annual cognitive and motor testing ante-mortem and wore wearable sensors prior to death, making this dataset a uniquely rich resource for studying cognitive and motor impairment across tissues and brain regions.
The ideal candidate will have a quantitative background (bioinformatics, computational biology, biostatistics, statistics, computer science, or applied mathematics), a demonstrated interest in solving biological problems, and experience with analyzing large-scale genomic data. A Ph.D. in a quantitative discipline is required, but candidates with a Ph.D. in biology or neuroscience and extensive experience in quantitative methods will also be considered. The candidate should have good knowledge of one programming language used for computational modeling (for example, R, Python, or Matlab). Experience with graph modeling, Bayesian statistics, or causal inference is a plus.
The candidate will join an integrated team of computational scientists, molecular biologists, human immunologists, and clinician scientists who come together to perform team-based projects. Each postdoctoral researcher leads their own project, making the ability to work both independently and collaboratively essential. The position offers a stimulating, multi-disciplinary environment with opportunities to collaborate across institutions, including ongoing shared projects with the New York Genome Center and Rush University in Chicago.
A PhD is required
Columbia University is an Equal Opportunity Employer / Disability / Veteran
Pay Transparency Disclosure
The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to departmental budgets, qualifications, experience, education, licenses, specialty, and training. The above hiring range represents the University?s good faith and reasonable estimate of the range of possible compensation at the time of posting.
