Nuanced Health Inc.
Computational Biologist, Metabolomics
Nuanced Health Inc., Los Angeles, California, United States, 90079
Computational Biologist, Metabolomics/Microbiome
Company Description
Nuanced Health is a seed-stage, venture capital-backed biotechnology company that is reimagining the drug development process in order to discover, develop, and evolve therapeutics. We believe that a better understanding of the biological heterogeneity among us can inspire novel therapeutics and maximize the efficacy of existing ones. At Nuanced Health, we combine
in vivo
techniques with computational methods to create a drug development process that addresses our unique biology and discovers treatments that work for everyone. We are a multidisciplinary company, motivated to build a mutualistic environment where engineers and scientists work synergistically to create a revolutionary product on a category-defining platform for the life sciences industry.
Nuanced Health is founded on enabling and integrating teams and systems to have a greater impact – a core principle that we apply toward our people and our product.
Job Description The ability to analyze and interrogate the diverse molecules in metabolomic data directly enables the success of Nuanced Health’s mission to change drug discovery. A critical aspect of that is the ability to incorporate analyses from mass-spectrometry based datasets with those from other high-throughput data in order to compile multi-omic results.
As part of the computational team, you will deliver research that directly impacts and supports the growth of the organization through the design, execution and analysis of experiments. You should be excited about analytical solutions that provide actionable insights from biological data. These results will be derived from robust, scalable, and reproducible cloud-based computational workflows that rely on fundamental biological concepts and integrate novel methods in bioinformatics or machine learning where appropriate.
As a Computational Biologist, Metabolomics/Microbiome, you will be primarily responsible for driving scientific progress as it relates to the metabolomic program as part of the larger platform. You would be joining a team of microbiologists, immunologists, researchers and computational scientists and engineers, so an ideal teammate is intentionally curious, highly adaptable, committed to learning, and passionate about innovation, all within a dynamic startup environment.
Roles and Responsibilities Lead experimental design and analysis of metabolomic, proteomic, and lipidomic data from diverse biological samples Design, build and refine the bioinformatics pipelines for mass-spectrometry based metabolomics, proteomics, and lipidomics to support scientific projects Apply established and novel methods to investigate complex biological samples Collaborate closely with teammates across multiple teams to drive multi-omic discovery research Skills and Qualifications PhD or MS and equivalent research experience in Bioinformatics/Computational Biology, Chemistry/Chemical Biology, Applied Math, Statistics, Engineering, Computer Science, or a related quantitative field with 2-5 years of industrial and/or academic research experience preferred but will consider strong candidates with less experience Experience utilizing or developing computational methods for processing and analyzing large-scale, data-independent acquisition (DIA) mass-spectrometry based metabolomic, proteomics, meta-metabolomic, or meta-proteomics datasets (e.g. PEAKS, MaxQuant, DiaNN, OpenMS, Spectronaut, Proteome Discoverer, xcms, MS-DIAL, MZMine, OpenMS, MarkerView, Compound Discoverer, LipidBlast, etc.) Experience integrating and/or analyzing multi-omic datasets Strong understanding of biochemistry and biology to facilitate analysis and interpretation of microbiome biology (e.g., protein interaction networks, immunoproteomics, systems biology, metabolomics, microbiome ecology) Familiarity with chemi-, protein-, and bio-informatic computational toolkits and packages (e.g. RDKit, pyOpenMS, pyteomics, Biopython, QIIME2, HUMAnN2, SciPy, etc.) Track record of publications or research Track record of working in cross-functional teams Proficient coding skills in R, Python, or other scientific programming language Experience with workflow managers (e.g. Nextflow, Snakemake, Cromwell, WDL, etc.) Experience with cloud-based/server-based computing (e.g. Amazon AWS, Microsoft Azure, Google Cloud Platform (GCP)) Ability to work in-person in our Los Angeles office
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in vivo
techniques with computational methods to create a drug development process that addresses our unique biology and discovers treatments that work for everyone. We are a multidisciplinary company, motivated to build a mutualistic environment where engineers and scientists work synergistically to create a revolutionary product on a category-defining platform for the life sciences industry.
Nuanced Health is founded on enabling and integrating teams and systems to have a greater impact – a core principle that we apply toward our people and our product.
Job Description The ability to analyze and interrogate the diverse molecules in metabolomic data directly enables the success of Nuanced Health’s mission to change drug discovery. A critical aspect of that is the ability to incorporate analyses from mass-spectrometry based datasets with those from other high-throughput data in order to compile multi-omic results.
As part of the computational team, you will deliver research that directly impacts and supports the growth of the organization through the design, execution and analysis of experiments. You should be excited about analytical solutions that provide actionable insights from biological data. These results will be derived from robust, scalable, and reproducible cloud-based computational workflows that rely on fundamental biological concepts and integrate novel methods in bioinformatics or machine learning where appropriate.
As a Computational Biologist, Metabolomics/Microbiome, you will be primarily responsible for driving scientific progress as it relates to the metabolomic program as part of the larger platform. You would be joining a team of microbiologists, immunologists, researchers and computational scientists and engineers, so an ideal teammate is intentionally curious, highly adaptable, committed to learning, and passionate about innovation, all within a dynamic startup environment.
Roles and Responsibilities Lead experimental design and analysis of metabolomic, proteomic, and lipidomic data from diverse biological samples Design, build and refine the bioinformatics pipelines for mass-spectrometry based metabolomics, proteomics, and lipidomics to support scientific projects Apply established and novel methods to investigate complex biological samples Collaborate closely with teammates across multiple teams to drive multi-omic discovery research Skills and Qualifications PhD or MS and equivalent research experience in Bioinformatics/Computational Biology, Chemistry/Chemical Biology, Applied Math, Statistics, Engineering, Computer Science, or a related quantitative field with 2-5 years of industrial and/or academic research experience preferred but will consider strong candidates with less experience Experience utilizing or developing computational methods for processing and analyzing large-scale, data-independent acquisition (DIA) mass-spectrometry based metabolomic, proteomics, meta-metabolomic, or meta-proteomics datasets (e.g. PEAKS, MaxQuant, DiaNN, OpenMS, Spectronaut, Proteome Discoverer, xcms, MS-DIAL, MZMine, OpenMS, MarkerView, Compound Discoverer, LipidBlast, etc.) Experience integrating and/or analyzing multi-omic datasets Strong understanding of biochemistry and biology to facilitate analysis and interpretation of microbiome biology (e.g., protein interaction networks, immunoproteomics, systems biology, metabolomics, microbiome ecology) Familiarity with chemi-, protein-, and bio-informatic computational toolkits and packages (e.g. RDKit, pyOpenMS, pyteomics, Biopython, QIIME2, HUMAnN2, SciPy, etc.) Track record of publications or research Track record of working in cross-functional teams Proficient coding skills in R, Python, or other scientific programming language Experience with workflow managers (e.g. Nextflow, Snakemake, Cromwell, WDL, etc.) Experience with cloud-based/server-based computing (e.g. Amazon AWS, Microsoft Azure, Google Cloud Platform (GCP)) Ability to work in-person in our Los Angeles office
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