Applications received after this date will be reviewed by the search committee if the position has not yet been filled.
Applications will continue to be accepted until this date, but those received after the review date will only be considered if the position has not yet been filled.
Bioinformatics Specialist- Krogan Lab
The Krogan Lab (http://kroganlab.ucsf.edu) is a highly collaborative laboratory focusing on the molecular networks underpinning infectious disease, carcinogenesis, and psychiatric disorders. The candidate will work closely with senior members of the Krogan Lab to apply the appropriate algorithms, computational and modeling techniques, and statistical methodologies to analyze and visualize data primarily generated through high-throughput proteomics experiments. The candidate will also have the opportunity to develop novel pipelines for analyzing and interpreting proteomics data, and integrating it with other types of data. This role is an excellent opportunity to learn a number of valuable, cutting-edge techniques while working with an ambitious and friendly research team. Our ideal applicant is a problem solver with a positive attitude, excellent organizational and interpersonal skills, and the ability to learn and implement methodology efficiently.
- A degree in bioinformatics, computer sciences, computational biology, statistics or similar.
- Junior rank: Bachelor’s degree
- Assistant/Associate Rank: Master’s degree, or Bachelor’s degree and 5-10 years of work experience in relevant field
- Full rank: PhD degree, or lower degree with 10+ years of work experience in relevant field.
- Strong computational skills and adherence to best practices
- Excellent teamwork skills and the ability to communicate effectively and collaboratively with students, postdoctoral fellows, staff, and faculty.
- Candidates must meet the requirements by the time of appointment.
- Post-graduate training in field
- Independent specialized research
- Computer programming skills in R, python or similar language.
- Understanding of large-scale proteomics data and placing it in a biological context
- Experience in generalized and/or linear mixed models, machine learning algorithms, experimental design, general statistical, and other commonly applied techniques in statistical omics data analysis.
- Skill in relational database design, implementation, optimization, and storage procedures.
UC San Francisco seeks candidates whose experience, teaching, research, or community service that has prepared them to contribute to our commitment to diversity and excellence. The University of California is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age or protected veteran status.
Please apply online at https://aprecruit.ucsf.edu/JPF02396, with CV and cover letter.
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