Computational Biologist

Added: 8/30/2021

REF: 13395

Contract: Permanent

Location: New York, United States

Exciting Life Sciences AI company thats aim is to digitize, decode and decipher human biology to prevent and reverse chronic diseases, cancer, and aging. We apply systems biology and advanced microbiology to deeply understand the origin and progression of disease using gene expression (mRNA) analysis with a state-of-the-art AI and machine learning platform. Our tests and clinical studies measure host/microbe gene expression, using which we discover disease biomarkers. Our consumer business uses these data analyses, and with insights from modern medical science our AI recommends a nutrition and lifestyle plan personalized for you. Our health science business also uses the biomarkers to develop predictive, diagnostic, and therapeutic solutions for a range of diseases, especially cancer, metabolic, and neurological diseases. Their rich data sources are unmatched in their depth and ability to provide insights. Our small interdisciplinary team is passionate about transforming the life science industry for the 21st century.

We are seeking a computational biologist that has expertise in biomedical sciences, ideally with a computational mindset, that is passionate about research pertaining to human genes and the microbiome. You will work in the biomedical research team which is responsible for the early clinical development of novel diagnostic and/or therapeutic programs from human studies to clinical proof-of-concept testing. Joining a multi-disciplinary team of data scientists and machine learning engineers, systems and computational biology scientists, as well as clinical experts, you will analyze our unique biological dataset with their phenotype metadata to discover biomarkers, demonstrate the effect of treatments, and participate in real world health science applications.

Responsibilities:

  • Apply computational and other data analysis techniques to explore biological hypotheses from large multi-omics heterogeneous datasets
  • Contribute to team effort in computational NGS analysis including transcriptomics, genomics and metatranscriptomics data analysis; including identifying fit-for-purpose tools and pipelines, implementing or/and working to streamline the workflow in suitable computing environment
  • Contribute to the development of innovative data integration pipelines to:
    • Act as a bridge between clinical, laboratory and computational teams to clarify and define the pathobiological pathways to answer questions impactful for projects
    • Provide bioinformatics support to ensure data quality and usability.
  • Maintain expertise in state-of-the-art data science and computational genomics methods

Skills and Qualifications:

  • MS/PhD in statistical genetics, bioinformatics, computational biology, or related field
  • 5+ years of work experience in computational biology
  • Extensive training/ experience in biological, computational and statistical sciences to analyze large-scale genetic datasets as well as leverage genomics and transcriptomic data to generate causal disease gene hypotheses
  • Experience applying sophisticated Systems Biology data analysis and actionable techniques to large datasets with various types of omics data
  • Proven track record and understanding of human genetics in complex disorders areas such as neurodegeneration, immuno-inflammation, cancer, metabolic disorders to identify potential biomarkers or therapeutic targets
  • Experience with integration of data from large human genetic datasets, including Differential Gene Expression (DGE), as well as data derived from various publicly available platforms (e.g. ENCODE, GTEx, TCGA)
  • Ability to apply new tools for the integrative analysis and visualization of multi-dimensional genomics datasets
  • Ability to work on high-performance computing system and manage cloud computing environments (e.g. AWS)
  • Expertise in computational tools and pipelines for data analysis of NGS data, including RNA-sequencing (WES and WGS are a plus)
  • Strong understanding of clinical/pathobiology functional readouts in complex disorders for identifying translatable targets based on human genetics
  • Familiarity with pathway databases and scientific/medical ontologies with ability to navigate complex concepts
  • Familiarity with nutritional science related to the gut microbiome and health/disease is a plus

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