Takeda Pharmaceuticals
Senior Scientist, Systems Biology
Takeda Pharmaceuticals, Boston, Massachusetts, us, 02298
At Takeda, we are a forward-looking, world-class R&D organization that unlocks innovation and delivers transformative therapies to patients. By focusing R&D efforts on three therapeutic areas and other targeted investments, we push the boundaries of what is possible in order to bring life-changing therapies to patients worldwide.Certified as a Global Top Employer, Takeda offers stimulating careers, encourages innovation, and strives for excellence in everything we do. We foster an inclusive, collaborative workplace, in which our teams are united by an unwavering commitment to deliver Better Health and a Brighter Future to people around the world.Are you looking for a patient-focused, innovation-driven company that will inspire you and empower you to shine? Join us as a Senior Scientist, Systems Biology in our Cambridge, MA location.Objective / Purpose:
Be part of a computational team focused on utilizing in silico and systems biology approaches to support Takeda drug discovery and development projects.Utilize advanced bioinformatics, computational, AI/ML, and graph learning techniques to analyze multi–omic and multi-modal data, and identify novel drug targets, biomarkers, and cellular mechanisms of action across the Gastroenterology and Inflammation portfolio.Evaluate the efficacy of potential target candidates through the application of state-of-the-art computational approaches; working closely with experimental, biology, computational genetics, data science, quantitative statistics, engineering, translational medicine, and biomarker teams.Report to the Computational Biology Group leader and collaborate with key stakeholders to drive innovative therapies for inflammatory bowel disease, chronic liver disorders, and chronic inflammatory indications in dermatology and rheumatology.Accountabilities:
Serve as a subject matter expert in projects requiring multi-omic and multi-modal analyses from preclinical and clinical studies to identify and execute biomarker studies, patient stratification, and identify novel drug targets/biomarkers.Use multimodal/foundational models including but not limited to clinical data, single-cell, and genomics.Develop AI/ML models, knowledge graphs and NLP pipelines; incorporate computational strategies with graph-neural networks, deep learning, multimodal fusion, transformer models, transfer learning, contrastive learning as appropriate.Present scientific reports in internal meetings in all settings and with participants of all levels of the organization, as well as for external audiences.Proactively identify complex obstacles, recommend and implement solutions using a diverse set of resources.Work collaboratively with data and quantitative scientists and data engineering groups to enhance our computational infrastructure, build on innovative C&SB solutions and intuitive multi-omics interface.Technical/Functional (Line) Expertise:
Strong knowledge of molecular biology and genomics.Biological knowledge in one or more areas of inflammation and fibrosis (IBD, chronic liver disorders, chronic inflammatory indications in dermatology and rheumatology).Demonstrated experience in large scale multi-omics (e.g. bulk or single-cell, spatial sequencing, proteomics, epigenetics, and more), multi-modal data integration, network analysis, and meta-analyses.Strong machine learning experience is preferred.Statistical analysis experience with working knowledge of regression analysis, multivariate data analysis, and linear/nonlinear mixed effects modeling is preferred.Demonstrated ability to integrate and analyze multimodal biomedical data.Background and work experience in graph-neural networks, deep learning, multimodal fusion, transformer models, transfer learning, contrastive learning.Experience in developing clinical knowledge graphs and working with NLP and retrieval-augmented generation pipelines.Experience with multimodal/foundational model development including but not limited to clinical data, single-cell, and genomics.Ability to independently solve scientific problems using multiple, state-of-the-art technologies and approaches.Experience with computational method evaluation, development, and implementation.Solid knowledge of Unix/Linux, command line interfaces, and fluency in some common scripting and/or programming language (e.g., R, Python, Perl, Java, C / C++) used for statistical and computational multi-omics analysis.Experience with high performance computing, relational databases (e.g., SQL), and cloud computing or distributed computing (Amazon Web Services).Education & Competencies:
PhD degree in Systems Biology, Bioinformatics or Computational Biology with 2+ years relevant experience, or MS with 8+ years relevant experience, or BS with 10+ years relevant experience.Previous industry experience is preferred and a strong background in applying computational and systems biology, including multi-omics data analyses, to research, translational and clinical programs with demonstrated ability to meet program objectives and timelines.Strong organizational and effective communication skills.This position is currently classified as “hybrid” by Takeda’s Hybrid and Remote Work policy.EEO Statement:
Takeda is proud in its commitment to creating a diverse workforce and providing equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, parental status, national origin, age, disability, citizenship status, genetic information or characteristics, marital status, status as a Vietnam era veteran, special disabled veteran, or other protected veteran in accordance with applicable federal, state and local laws, and any other characteristic protected by law.Locations:
Boston, MAWorker Type:
EmployeeWorker Sub-Type:
RegularTime Type:
Full time
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Be part of a computational team focused on utilizing in silico and systems biology approaches to support Takeda drug discovery and development projects.Utilize advanced bioinformatics, computational, AI/ML, and graph learning techniques to analyze multi–omic and multi-modal data, and identify novel drug targets, biomarkers, and cellular mechanisms of action across the Gastroenterology and Inflammation portfolio.Evaluate the efficacy of potential target candidates through the application of state-of-the-art computational approaches; working closely with experimental, biology, computational genetics, data science, quantitative statistics, engineering, translational medicine, and biomarker teams.Report to the Computational Biology Group leader and collaborate with key stakeholders to drive innovative therapies for inflammatory bowel disease, chronic liver disorders, and chronic inflammatory indications in dermatology and rheumatology.Accountabilities:
Serve as a subject matter expert in projects requiring multi-omic and multi-modal analyses from preclinical and clinical studies to identify and execute biomarker studies, patient stratification, and identify novel drug targets/biomarkers.Use multimodal/foundational models including but not limited to clinical data, single-cell, and genomics.Develop AI/ML models, knowledge graphs and NLP pipelines; incorporate computational strategies with graph-neural networks, deep learning, multimodal fusion, transformer models, transfer learning, contrastive learning as appropriate.Present scientific reports in internal meetings in all settings and with participants of all levels of the organization, as well as for external audiences.Proactively identify complex obstacles, recommend and implement solutions using a diverse set of resources.Work collaboratively with data and quantitative scientists and data engineering groups to enhance our computational infrastructure, build on innovative C&SB solutions and intuitive multi-omics interface.Technical/Functional (Line) Expertise:
Strong knowledge of molecular biology and genomics.Biological knowledge in one or more areas of inflammation and fibrosis (IBD, chronic liver disorders, chronic inflammatory indications in dermatology and rheumatology).Demonstrated experience in large scale multi-omics (e.g. bulk or single-cell, spatial sequencing, proteomics, epigenetics, and more), multi-modal data integration, network analysis, and meta-analyses.Strong machine learning experience is preferred.Statistical analysis experience with working knowledge of regression analysis, multivariate data analysis, and linear/nonlinear mixed effects modeling is preferred.Demonstrated ability to integrate and analyze multimodal biomedical data.Background and work experience in graph-neural networks, deep learning, multimodal fusion, transformer models, transfer learning, contrastive learning.Experience in developing clinical knowledge graphs and working with NLP and retrieval-augmented generation pipelines.Experience with multimodal/foundational model development including but not limited to clinical data, single-cell, and genomics.Ability to independently solve scientific problems using multiple, state-of-the-art technologies and approaches.Experience with computational method evaluation, development, and implementation.Solid knowledge of Unix/Linux, command line interfaces, and fluency in some common scripting and/or programming language (e.g., R, Python, Perl, Java, C / C++) used for statistical and computational multi-omics analysis.Experience with high performance computing, relational databases (e.g., SQL), and cloud computing or distributed computing (Amazon Web Services).Education & Competencies:
PhD degree in Systems Biology, Bioinformatics or Computational Biology with 2+ years relevant experience, or MS with 8+ years relevant experience, or BS with 10+ years relevant experience.Previous industry experience is preferred and a strong background in applying computational and systems biology, including multi-omics data analyses, to research, translational and clinical programs with demonstrated ability to meet program objectives and timelines.Strong organizational and effective communication skills.This position is currently classified as “hybrid” by Takeda’s Hybrid and Remote Work policy.EEO Statement:
Takeda is proud in its commitment to creating a diverse workforce and providing equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, parental status, national origin, age, disability, citizenship status, genetic information or characteristics, marital status, status as a Vietnam era veteran, special disabled veteran, or other protected veteran in accordance with applicable federal, state and local laws, and any other characteristic protected by law.Locations:
Boston, MAWorker Type:
EmployeeWorker Sub-Type:
RegularTime Type:
Full time
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