Dalton Bioanalytics is a UCLA spin-off startup digitizing the biochemical composition of blood, cells, and other biological samples. For the first time in history, Dalton has developed an all-inclusive assay using Mass Spectrometry—enabling the simultaneous analysis of diverse molecules such as proteins, lipids, electrolytes, nutrients, environmental chemicals, drugs, and other small molecules. We are developing our platform using this technology to empower researchers and scientists to understand and discover new and important biochemical insights into bioprocessing, biomarker discovery, pharmaceuticals, foods, and diagnostics.
We are seeking an individual to assist with the analysis of multi-omic mass spectrometric data and to help develop our data analysis platform. Applicants must be comfortable working with large -omics datasets that encompass projects from diverse areas of research. Applicants must be self-motivated to research new analysis techniques to aid in laboratory efforts and be able to effectively communicate both results and methodologies to colleagues and collaborators.
• Develops theoretical and numerical models, algorithms, and graphical interfaces.
• Implements dimensionality reduction, clustering, regression, and machine learning analyses.
• Coordinates the development of user interfaces and data access services to archive large datasets and enable researchers to access and explore complex data in a centralized database.
• Oversees and coordinates formal quality review and analysis of scientific data and identifies appropriate corrective actions.
• Develops and/or works with high performing parallel computers and visualization systems to enhance computation and analysis or modeling.
• Authors results and presents findings at high-level meetings and scientific conferences.
• Reviews and critiques reports and analysis of other research staff.
• Conducts ongoing periodic and final analyses of data.
• PhD-level training in Bioinformatics or Biostatistics
• First-hand experience in algorithm development
• Experience with R and/or Python
• Strong communication skills
• Rigorous scientific standards
• Creative (outside-of-the-box) problem solving skills
• Experience with processing and analyzing -omics data
• Experience with data mining and machine learning
• Experience with LC-MS, Proteomics and/or Metabolomics analyses and software
• Knowledge in chemistry
• Professional software development experience
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