HOW TO APPLY

A cover letter is required for consideration for this position and should be attached as the first page of your resume. The cover letter should address your specific interest in the position and outline skills and experience that directly relate to this position.

REQUIRED QUALIFICATIONS*

• Bachelor’s degree in Computer Science, a related field or equivalent experience, along with 1 to 2 years systems analysis/programming activities in a business environment.
• Solid Java and/or Python programming skills
• Solid data structure and algorithms knowledge
• Experience with building Java-based user interfaces, web servers, and application programming interfaces.

DESIRED QUALIFICATIONS*

• Experience with implementing and running data analysis pipelines on Windows, Linux, and Cloud computing
• Experience with developing web frameworks such as Spring and Grails
• Undergraduate or graduate coursework in chemistry and/or physics, and biology
• Statistical analysis and data visualization

Alexey Nesvizhskii’s laboratory in the Department of Pathology is looking for a new member of the team to assist with the development of computational software for proteomics data analysis. This individual will assist with the maintenance and development of the existing computational tools and algorithms developed in the lab for processing and visualizing proteomics data (known as FragPipe computational platform). The individual will work in close collaboration with other members of the lab, including Ph.D. students, post-doctoral research fellow, and research faculty. There will be opportunities to contribute to new algorithm developments as well. The successful candidate will have a bachelor’s degree or higher in a technical field (computer science, bioinformatics etc.), expert programming skills (especially in Java), and demonstrated experience with software development and maintenance. Undergraduate or graduate level coursework in physics, chemistry, and signal processing is highly desirable, as the candidate will be expected to understand the underlying proteomics data generated using mass spectrometry-based technologies.