Olaris is looking for high performing and outgoing individuals to join our team, come join us.
If you like diving into data, love R, have used statistical and machine learning techniques to find new insights into complex biological problems and are passionate about having a profound impact on an early stage company we want to meet you. To learn more about this position please submit your resume and cover letter to careers@olarisBoR.com
Degree in CS, Machine Learning, Statistics or related field
2-5 years related experience
Deep understanding of statistics, machine learning, and other analytical methods to gain biological insight from large datasets
Experience with R, Ruby, Matlab, Python
**Olaris is not currently hiring for this position. However if you're a data science rock star we encourage you to submit a resume and we will alert you to new openings.
Do you believe metabolic processes provide the basis to understand complex biological problems? Do you get excited about developing novel NMR and MS methods that push the boundaries of what metabolites we can detect? Are you passionate about having a profound impact on an early stage company? If so, we want to meet you. Olaris is looking for high-performing and outgoing individuals to join our research and development team. The successful candidate(s) will be responsible for a broad range of research activities including preparing samples, running custom NMR experiments, and data analysis. There will be opportunities to develop new NMR and MS methodologies to integrate into our platform. To learn more about this position please submit your resume and cover letter to careers@olarisBoR.com
M.S. or PhD Degree in Biological Sciences, Chemical Biology, Biophysics, or related field
2-5 years related NMR experience required, additional MS knowledge ideal
Deep understanding of metabolism, biochemical mapping and network analysis
Knowledge of NMR theory, pulse programs and data analysis including 1D, 2D and 3D experiments
Experience with NMRPipe, Chenomix, MNova and processing NUS data
Familiarity with statistics and bioinformatics tools