At Sage Bionetworks, we believe that we can learn more by learning from each other. By improving the way scientists collaborate, we help to make science more effective. We partner with researchers, patients, and healthcare innovators to drive collaborative data-driven science to improve health. Making science more open, collaborative, and inclusive ultimately advances biomedicine.
We are looking for a Research Scientist to join our Neurodegeneration Research group. You will contribute to computational biology research projects within the National Institute on Aging’s Accelerating Medicine Programs- Alzheimer’s Disease (AMP-AD) consortium. You will provide oversight and mentorship in support of AD-consortia research efforts as well as perform and publish independent research. Research areas may include 1) identification of variants underlying AD genetic disease risk, 2) developing methods to identify AD subtypes based on integrative data analysis across omic and clinical data, and 3) performing integrated analysis of proteomic and RNA-seq data to build predictive models of protein expression in datasets lacking proteomic data. Enthusiasm for the application of computational biology and technology to enable open, collaborative, and reproducible biomedical research is essential.
What you’ll be doing:
- Performing independent research from inception to publication on genetic and genomic contributions to Alzheimer’s Disease.
- Crafting and developing algorithms for interrogating and interpreting complex genomic data.
- Coordinating collaborative research across multi-investigator working groups.
- Working with clinicians, biologists, and other bioinformaticians in academia and industry to develop bioinformatic analyses and visualizations of genomic data.
- Writing technical documentation for a scientific audience, authoring scientific papers for peer reviewed journals, and presenting work at scientific conferences.
- Training and mentoring scientists and research associates.
We’d love to hear from you if you:
- Have a Ph.D. in Computational Biology, Bioinformatics, Neuroscience, Computer Science, or related discipline; or another scientific degree with commensurate experience.
- Have experience working with high dimensional genomic data, such as sequencing data, gene expression, genotype, CNV and/or data from other high-throughput biological technologies.
- Demonstrate excellence in research with evidence of advancing an area of computational biology.
- Are proficient in R or Python.
- Understand advanced machine learning or statistical techniques, such as probabilistic graphical models, Bayesian inference, and optimization methods.
- Have excellent written and verbal communication skills.
- Have strong collaboration and teamwork skills.
- Are passionate about open science, reproducible research, and collaboration.