Associate Specialist Full-time

Associate Specialist

The Quantitative Biosciences Institute is now recruiting an Associate Specialist. The successful candidate will lead the computational efforts of developing and applying methods for applying proteomics and genetics data collected in situ for integrative structure modeling. Critical aspects of the research include: (1) Designing and executing methods to integrate data from different sources, including developing a Bayesian Hierarchical Modeling framework; (2) using integrative modeling approaches to characterize heterogeneous protein assemblies structures and dynamics; (3) developing methods for modeling proteins assemblies based on cross-linking mass spectrometry data, including from crosslinkers with novel chemistries; (4) modeling the post-synaptic density using integrative methods; and (5) writing manuscripts and applications for federally sponsored research, and presenting our research at scientific conferences.

Required Qualifications:

• A master's degree (or equivalent degree) in chemistry, biophysics, computational biology, or a related area, or five to ten years of relevant experience.
• Experience in integrative modeling approaches
• Familiarity with the data generation and analysis process of proteomics data such as HDX and cross-linking mass-spectrometry.
• Proficiency in using and developing molecular modeling software
• A demonstrated track record of effectively using quantitative approaches to biological problems
• Proficiency in computational methods and adherence to best practices
• Demonstrated experience as a research project leader
• Manage multiple diverse and collaborative projects between multiple laboratories
• High productivity and successful record publishing in high-impact journals

Preferred Qualifications:

• Ph.D.
• Post-graduate training in field
• Understanding of large-scale proteomics data and placing it in a biological context
• Experience in Bayesian statistics, machine learning/artificial intelligence algorithms, and other commonly applied techniques in the statistical -omics data analysis
• Expertise in large scale data handling
• Community outreach