We seek applicants for a Scientific Programmer to join the larger bioinformatics group at the Lewis-Sigler Institute for Integrative Genomics and the Center for Quantitative Biology. The ability to analyze large volumes of data and to separate signal from noise within these data is critical to successful biological research today. We are looking for an Application Delivery Specialist who can work closely with biologists to implement algorithms and apply statistical methods to analyze vast amounts of genome-wide data.
Specific duties include:
-Implement data analysis algorithms as requested by faculty and staff
-Consult and advise biological researchers on best methods available to analyze and interpret their data and assist in implementation
-Design, develop, implement, and document software required for biological data analysis and for biological databases, including tools for loading, searching, visualizing, and analyzing data
-B.S. in math, computer science, statistics, or related field
-3-5 years of relevant experience
-Experience with writing robust, complete software tools, from design to production
-Strong math/statistics background. Particularly relevant is familiarity with algorithms typically used in biological data analysis such as Hidden Markov Models, clustering algorithms, etc.
-Ability to quickly and efficiently implement algorithms and statistical methods
-Ability to work productively in a team environment, communicates effectively with people of varying technical backgrounds, and adjusts to the rapidly changing needs of researchers
-Experience with image analysis, data mining, and signal processing
-Experience with Matlab or R statistical analysis packages
-Background and/or interest in biology and genomics
-Experience with web application development
-Experience utilizing large compute clusters
Please apply via the Jobs at Princeton site - Requisition ID # 1300234
The final candidate will need to pass a background check.
Princeton University is an Equal Opportunity/Affirmative Action Employer and in keeping with our commitment, encourages women, minorities, persons with disabilities, and Vietnam-era and disabled veterans to apply.