Job Description

Job Description

Job Description

Contact: Neisha Camacho/Terra Parsons -

No 3rd party agencies

The Position: Reporting to the Bioinformatics & Systems Biology Leader, the Translational Bioinformatics Scientist will leverage their strong research experience and computational skills to work on biomarker discovery and mechanism understanding in disease prognosis/diagnosis and responses to intervention in support of our entire clinical development portfolio. You will play an important role to support the success of clinical trial development, product licensure, and implementation with the opportunity to impact diseases that affect millions disproportionally in low- & middle-income countries. You will be a key partner to our product development teams and will work collaboratively with the biomarker, biometrics, clinical development, and discovery groups to advance novel interventions against our diseases of interest. The successful candidate will primarily work on multi-scale, multi-dimensional data generated from the state-of-the-art assay technologies and develop/leverage cutting-edge statistical and bioinformatics methods to drive Translational Medicine research that bridges between early discovery and late-stage product development.

Responsibilities :

• Develop analytics pipelines for a range of varied types of high-dimensional biomarker data, including but not limited to data from next generation sequencing, flow cytometry, mass spectrometry, 16S rRNA sequencing, or imaging.
• Work collaboratively with our internal and external teams to conduct nonclinical/clinical data analysis, data harmonization, data visualization and methodology benchmarking.
• Support strategic planning for biomarker data analysis in support of exploratory biomarker strategies in clinical trial design.
• Manage and improve the bioinformatics team’s code and data repository and training documents.
• Work with IT and biometric teams to establish and maintain an automated workflow for data acquisition and processing in a cloud-based environment.
• Be accountable for data interpretation, presentation and manuscript preparation for the analysis results generated from our studies.
• The candidate will be passionate about scientific discovery with the data-driven approach and be excited to work at the interface between biomarker scientists, biostatisticians and clinical researchers.
• Work with clinical biostatisticians and bioassay scientists to validate reproducibility of the predictive biomarker models prior to translating to clinical implementation.

Qualifications :

• PhD with +4-year experience in Computational Biology, Bioinformatics, Statistics, Computational Sciences, or Biomedical/Biological Engineering, or MS in a related field with 10 years of related experience.
• Strong scientific understanding of Molecular Biology, Immunology, Microbiology or Genomics.
• Strong experience in processing and analyzing data from high-throughput technologies such as next generation sequencing, flow cytometry, or mass spectrometry, and understanding of pathway/network analyses and gene/cell/immune system regulation.
• Excellent programming skills across multiple languages such as Python and R.
• Strong background in statistical fundamentals and analysis.
• Demonstrated experience in cloud-based parallel computing environment and data science development platforms, such as GitHub/GitLab, Jupyter, R shiny, Anaconda, and Docker, is required.
• Solid experience applying multivariate statistical approaches such as machine learning, and deep learning tools to model biological data is a big plus.
• Experience in infectious disease is preferred.
• Experience in microbiome data analysis is a plus.
• Capability for independent thinking, innovative analyses of large biological datasets.
• Ability to communicate technical information and scientific concepts in a clear manner.
• Personal attributes: self-driven, fast learner, problem solver. Must be able to meet deadlines consistently.

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