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Bioinformatics Programming Specialist

2 months ago

San Francisco, California, United States University of California , San Francisco Full time
Position Overview

Bioinformatics Programming Specialist

The University of California, San Francisco is seeking a dedicated individual to enhance our bioinformatics and computational biology team. Our laboratory is characterized by a collaborative and innovative environment, focusing on the application of proteomics, functional genomics, and computational biology to decode complex biological and biomedical challenges.

We are looking for candidates who possess the enthusiasm, motivation, and inquisitiveness necessary for continuous learning in the diverse fields of biology, biological research systems, and computational methodologies that we utilize or develop within our lab.

Key Responsibilities:

  • Utilizing existing analytical pipelines to process proteomics and other 'omics datasets, identifying proteins, interactions, pathways, networks, and cellular mechanisms related to health and disease.
  • Adapting current analytical pipelines; innovating or integrating new methodologies; and assessing new or enhanced techniques.
  • Creating computational tools and ensuring the maintenance of computational infrastructure to facilitate data analysis and management within the laboratory.

Qualifications:

  • Junior Specialist: A bachelor's degree (or equivalent) or a minimum of four years of relevant research experience.
  • Assistant Specialist: A master's degree or a bachelor's degree accompanied by three or more years of research experience.
  • Proficiency in data analysis and graphical representation using the R programming language, or a similar language such as Python with a willingness to learn R.
  • Experience analyzing 'omics datasets, which typically involve thousands of measurements across various conditions and replicates.
  • Familiarity with biological systems and research methodologies.
  • Strong communication skills and the ability to collaborate effectively within a team.
  • Applicants must meet the necessary qualifications at the time of appointment.
  • Application materials should clearly outline qualifications and/or any pending credentials upon submission.

Preferred Skills/Experience:

  • Understanding of biological networks, including protein interaction networks, and their visualization.
  • Knowledge of linear regression models and ANOVA.
  • Experience with null hypothesis testing and p-value adjustments for multiple comparisons, such as FDR estimation.
  • Familiarity with data clustering techniques.
  • Experience with dimensionality reduction methods (e.g., PCA, SVD, NMF).
  • Understanding of over-representation or enrichment analysis, including hypergeometric tests or GSEA.
  • Experience with SQL and database design.
  • Familiarity with R/Shiny or other web-based data analysis tools.
  • Experience in a Linux or Unix-like command line environment.
  • Knowledge of machine learning algorithms and their application in biological contexts.
  • Familiarity with artificial intelligence systems for biological problem-solving, such as Alphafold.

Problem-Solving Skills:

Common Challenges:

Assessing the quality of individual mass spectrometry runs, determining which should be excluded to enhance result accuracy.

Correcting data or figure formats to meet publication standards through translation, adjustment, or reformatting.

Less Frequent/More Complex Issues:

Translating genes from non-human models to their orthologous human counterparts.

Addressing normalization issues in protein intensity across mass spectrometry runs that fail to account for systematic technical differences.

Collaboration with Supervisors:

Resolving compatibility issues with software versions on shared resources that require updates.

Addressing disagreements among collaborators regarding appropriate analysis methodologies, necessitating the selection and justification of a unified approach.

Interested candidates are encouraged to submit their application materials, including a CV, cover letter, and references.

About UC San Francisco:

As an employee of the University, adherence to all applicable policies and collective bargaining agreements is required. UC San Francisco is committed to diversity and excellence, seeking candidates whose experiences, teaching, research, or community service have prepared them to contribute to this mission. The University of California is an Equal Opportunity/Affirmative Action Employer, ensuring that all qualified applicants receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or protected veteran status.