Closing Date: 15 March 2021
The research program in the Nicoli lab focuses on combining genetics and developmental biology approaches to understand how the regulation of gene expression governs cardiovascular phenotypes. More specifically this position aims to develop computational methodologies and designing integrative data science approaches to study 1) how genomic and phenotypic variations develop in the neurovascular system1,2, 2) how the cardiovascular system responds and adapts to environmental perturbations via gene expression canalization3,4, and 3) how hematopoietic stem cells gene program is regulated during transdifferentiation from the endothelium (BioRxiv 602912).
This individual will design algorithms, apply statistical methods, innovate ways to analyze, integrate, visualize, and interpret a wealth of systems data that will directly inform discovery experiments and target advancement projects in the areas of cardiovascular biology, genetics and development. This individual will use computational and statistical tools to analyze bulk and single-cell transcriptional analyses, and work closely with experimental biologists to interpret data. In addition, this individual will develop new algorithms to analyze genomic data, transcriptional data and data sets from screens. The individual will also develop methods for data visualization and integrating diverse types of data. The successful candidate should demonstrate initiative and be invested in the success of research projects. The individual will have enthusiasm for taking a hands-on, problem-solving approach, learning on the job, and collaborating with research scientists and associates in an informal collegial work.
The Nicoli Lab is part of the Yale Cardiovascular Research Center at Yale Medicine and Genetics and it is supported by multiple NIH funded research projects. Each postdoctoral scientist in the lab will receive comprehensive and personalized training in research and career development and will have extensive opportunities for independent and collaborative research. The Nicoli lab has established close collaborations with multiple labs both within and outside Yale university, including departments of Genetics, Pharmacology, Biomedical Engineering, the Yale RNA center, and the Yale Stem Cell Center.
- To qualify for the positions, a Ph.D. or equivalent degree in any quantitative science, including but not limited toBioinformatics, Computational Biology, Applied Mathematics, Statistics, Physics, Chemistry, Computer Science, Data Science, Engineering or a related field is required;
- Proficient in Python & R programming;
- Strong quantitative background (e.g., machine learning, statistical modeling, etc.) or computational genomics experience (e.g., next-generation sequencing analysis, etc.);
- Excellent communication and teamwork skills;
- At least one peer-reviewed publication written in English in the previous area of research;
- At least two referee names and contact information.
Contact firstname.lastname@example.org to apply.
1 Fortuna, V. et al. Vascular Mural Cells Promote Noradrenergic Differentiation of Embryonic Sympathetic Neurons. Cell Rep 11, 1786-1796, doi:10.1016/j.celrep.2015.05.028 (2015).
2 Ristori, E. et al. A Dicer-miR-107 Interaction Regulates Biogenesis of Specific miRNAs Crucial for Neurogenesis. Dev Cell 32, 546-560, doi:10.1016/j.devcel.2014.12.013 (2015).
3 Moro, A. et al. MicroRNA-dependent regulation of biomechanical genes establishes tissue stiffness homeostasis. Nat Cell Biol 21, 348-358, doi:10.1038/s41556-019-0272-y (2019).
4 Kasper, D. M. et al. MicroRNAs Establish Uniform Traits during the Architecture of Vertebrate Embryos. Dev Cell 40, 552-565 e555, doi:10.1016/j.devcel.2017.02.021 (2017).