WorkLlama, Inc.
Data Scientist - Translational Neuroscience Analytics
WorkLlama, Inc., Cambridge, Massachusetts, us, 02140
Role overview:
The qualified individual will be an expert in the field of Computational Biology & Data Science. They will have deep expertise in the application of computational approaches to analyze multi-modal biological datasets to decode causal biology with the goal of identifying novel drug targets and diseases biomarkers in neurodegenerative diseases. In this role, they will work alongside other computational biologists and data scientists to inform all stages of our Neuroscience drug development pipeline. As such, they will leverage cutting-edge AI/ML and analytics approaches to integrate human genetics, multi-scale molecular profiles of patient-derived samples, and functional genomics data derived from a wide-array of preclinical models to address challenging problems in early target discovery, characterization of mechanisms of action and discovery of patient stratification biomarkers. They will be expected to operate in a collaborative environment, working with cross-functional teams of computational biologists, data scientists, bench scientists and clinical colleagues.
What you will do:
Leverage Bioinformatics, System Biology, Statistics and Machine Learning methods to analyze high-throughput omics datasets, with a specific focus on novel target and biomarker discovery in Neuroscience.
Lead computational analyses and data integration projects involving genomic, transcriptomic, proteomic, and other multi-omics data.
Provide high-quality data analysis and timely support for target and biomarker discovery projects supporting the organization’s growing Neuroscience portfolio.
Keep up-to-date with the latest bioinformatics analysis methods, software, and databases, integrating new methodologies into existing frameworks to enhance data analysis capabilities.
Work with experimental biologists, functional area experts, and clinical scientists to support drug discovery and development programs at various stages.
Provide computational biology /data science input in research strategy and experimental design, provide bioinformatics input, and assist in interpreting results from both in-vitro and in-vivo studies.
Communicate study results effectively to the project team and wider scientific community through written and verbal means, including proposals for further experiments, presentations at internal and external meetings, and publications in leading journals.
Required Education:
PhD in Computational Biology, Bioinformatics, Biostatistics, Computer Science, or a related discipline.
MSc in Computational Biology, Bioinformatics, Biostatistics, Computer Science, or a related discipline, with a minimum of 5 years of academic or industry experience.
Required Experience and Skills:
Demonstrated expertise in bioinformatics, computational biology, machine learning, multi-omics data analysis, biological data integration and interpretation.
Extensive and demonstrated experience in the computational analysis of multi-modal and multi-scale (e.g. single cell, spatial) molecular profiles of patient-derived samples.
Proficient in one or more programming languages (e.g., Python, R) and competent with HPC environments and/or cloud-based platforms.
Experience with version control systems, such as Git (e.g., Github).
Good working knowledge of public and proprietary bioinformatics databases, resources and tools.
Familiarity with public repositories of DNA, RNA, protein, single-cell and spatial profiling data.
Ability to critically evaluate scientific research and apply novel informatics methods in translational applications.
Strong problem-solving skills, self-motivated, attention to detail, and ability to handle multiple projects.
Proven ability to conduct research individually and collaboratively.
Proven track record of contributions to peer-reviewed publications in the field of bioinformatics or computational biology.
Excellent communication skills (written, presentation, and oral).
Preferred qualifications
Experience in analyzing neuroscience datasets and working knowledge of neuroscience, especially neurodegenerative diseases.
In-depth understanding of drug target and biomarker identification in an industry setting
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What you will do:
Leverage Bioinformatics, System Biology, Statistics and Machine Learning methods to analyze high-throughput omics datasets, with a specific focus on novel target and biomarker discovery in Neuroscience.
Lead computational analyses and data integration projects involving genomic, transcriptomic, proteomic, and other multi-omics data.
Provide high-quality data analysis and timely support for target and biomarker discovery projects supporting the organization’s growing Neuroscience portfolio.
Keep up-to-date with the latest bioinformatics analysis methods, software, and databases, integrating new methodologies into existing frameworks to enhance data analysis capabilities.
Work with experimental biologists, functional area experts, and clinical scientists to support drug discovery and development programs at various stages.
Provide computational biology /data science input in research strategy and experimental design, provide bioinformatics input, and assist in interpreting results from both in-vitro and in-vivo studies.
Communicate study results effectively to the project team and wider scientific community through written and verbal means, including proposals for further experiments, presentations at internal and external meetings, and publications in leading journals.
Required Education:
PhD in Computational Biology, Bioinformatics, Biostatistics, Computer Science, or a related discipline.
MSc in Computational Biology, Bioinformatics, Biostatistics, Computer Science, or a related discipline, with a minimum of 5 years of academic or industry experience.
Required Experience and Skills:
Demonstrated expertise in bioinformatics, computational biology, machine learning, multi-omics data analysis, biological data integration and interpretation.
Extensive and demonstrated experience in the computational analysis of multi-modal and multi-scale (e.g. single cell, spatial) molecular profiles of patient-derived samples.
Proficient in one or more programming languages (e.g., Python, R) and competent with HPC environments and/or cloud-based platforms.
Experience with version control systems, such as Git (e.g., Github).
Good working knowledge of public and proprietary bioinformatics databases, resources and tools.
Familiarity with public repositories of DNA, RNA, protein, single-cell and spatial profiling data.
Ability to critically evaluate scientific research and apply novel informatics methods in translational applications.
Strong problem-solving skills, self-motivated, attention to detail, and ability to handle multiple projects.
Proven ability to conduct research individually and collaboratively.
Proven track record of contributions to peer-reviewed publications in the field of bioinformatics or computational biology.
Excellent communication skills (written, presentation, and oral).
Preferred qualifications
Experience in analyzing neuroscience datasets and working knowledge of neuroscience, especially neurodegenerative diseases.
In-depth understanding of drug target and biomarker identification in an industry setting
#J-18808-Ljbffr