This position reports directly to Dr. James Costello in the Department of Pharmacology, and will be responsible for developing computational methods to disentangle co-occurring conditions using multi-omics data in Down syndrome. The position will be jointly mentored by Dr. Casey Greene in the Department of Biomedical Informatics and is funded by the NIH, INCLUDE (INvestigation of Co-occurring conditions across the Lifespan to Understand Down syndromE) Project. The ideal candidate will have a background in multi-omic data processing, analysis, and modeling, with a strong interest in understanding molecular mechanisms of disease. The position will be highly collaborative working with a diverse group of researchers. It will also be expected that this position will publish academic research articles and contribute to lab efforts in mentoring students, grant writing, and manuscript review.
The position is a postdoctoral research fellow and the position will be responsible for developing and executing research plans designed in collaboration with Drs. Costello, Greene, and other Down syndrome researchers. The research plans will include multi-omic and clinical data collection, processing, and harmonization. Plans will then include the development of novel computational/biostatistical/machine learning methods for the integration of these data and the synthesis of hypotheses around the molecular mechanisms that drive the co-occurring condition of interest. The position is highly collaborative, thus the position will be responsible for interacting with graduate students, other postdoctoral researchers, and faculty members. The position will be expected to lead independent research projects, including data management and writing manuscripts. In leading the research project, this position will assist in the training of graduate students.
Minimum Qualifications:
-Graduation from an accredited college or university with a PhD in one of these fields of study: Computational Biology, Bioinformatics, Biomedical Informatics, Computer Science, Physics, Engineering, or an equivalent degree.
-The successful completion of a research project as evidenced by at least one first-authored and published manuscript.
Preferred Qualifications:
-Proven experience in methods development for multi-omic data analysis
-Proven experience in disease research
-A track record in Down syndrome research
-Demonstrated ability to train researchers in bioinformatics skills and techniques
-A track record of contributions to proposals for research funding
-A track record of public speaking for presenting research findings in an academic setting
-Interest in developing new analytical workflows for emerging technologies (e.g., multiplexed ion beam imaging or single cell technologies)
-Excellent communication skills
-Proven ability to work independently within a research lab
-Demonstrated excellence in software development, including an active GitHub account, or equivalent
-It is expected that research findings will be written in an academic manuscript
Please apply here: cu.taleo.net/careersection/2/jobdetail.ftl?job=27356&lang=en