The Rube Lab at University of California, Merced is looking for an ambitious Postdoctoral Scholar to carry out a project that leverages compressed sensing to accelerate proteomics research. The position is NSF-funded, and the scholar will work closely with Drs. Tomas Rube (UC Merced) and Marko Jovanovic (Columbia University). This research opportunity will primarily focus on developing computational methods for designing and interpreting pooled high-throughput experiments. The work will be done in close collaboration with a larger team that integrates computational and experimental technologies into a platform that detects protein-protein interactions with drastically increased scale and efficiency.
The ideal candidate has experience or a strong desire to build bioinformatics tools for interpreting high-throughput mass spectrometry or DNA sequencing data. The Rube lab is an inclusive and collaborative environment that prioritizes team science. The postdoctoral scholar will have opportunities to both contribute to and lead research projects.
Responsibilities of this position will include:
- Develop state-of-the-art methods for designing and interpreting compressive measurements.
- Work closely with experimental scientists to iteratively improve the platform.
- Disseminate results through high-quality publications in peer-reviewed journals and at national and international conferences.
- Mentor undergraduate and graduate students in the lab.
- Participate in professional development activities.
- Ensure best practices in data and project management.
- Stay current with technological advancements and apply this knowledge to enhancing ongoing research initiatives.
Basic qualifications:
A PhD (or equivalent international degree), completed before the start date of the position, in a relevant field, such as bioinformatics, statistics, genomics, applied mathematics, computer science, electrical engineering or physics.
Preferred qualifications
- A deep understanding of statistical modeling, inference, and compressed sensing.
- Experience deriving biological insights from large datasets, including mass-spectrometry and DNA-sequencing datasets.
- Proficiency in Python or another general-purpose programming language and experience with high-performance computing.
- Publications in peer-reviewed scientific journals.
Submit application at aprecruit.ucmerced.edu/JPF02022