Sr. Scientist, Neuroscience Computational Biology
TakedaAbout the role
By clicking the “Apply” button, I understand that my employment application process with Takeda will commence and that the information I provide in my application will be processed in line with Takeda’s Privacy Notice and Terms of Use. I further attest that all information I submit in my employment application is true to the best of my knowledge.
Job Description
Objective / Purpose:
Join Takeda as a Senior Scientist, Computational Biology, and become part of a global team that leverages cutting-edge computational biology and AI/ML techniques to rigorously identify and evaluate disease-target-biomarker relationships, and derives novel insights for drug discovery, indication expansion, and biomarker development. As a Senior Scientist within the Neuroscience computational group, you will be a part of the Computational Sciences department and will engage with key stakeholders across diverse Takeda R&D teams (e.g., discovery biology, translational medicine, biomarker sciences, clinical development, and AI/ML), as well as with CROs and academic partners. You will apply expertise in bioinformatics, genomics, machine learning, and computational biology to integrate and analyze pre-clinical and clinical, internal and public multi-omics datasets, to accelerate Takeda’s Neuroscience pipeline and bring transformative medicines to patients.
Accountabilities:
- Serve as a subject matter expert in projects requiring multiomic and high-dimensional data analyses within Neuroscience portfolio at late preclinical and clinical stages including neurodegenerative, neuromuscular and sleep disorders.
- Apply state-of-the art bioinformatics, AI/ML and computational approaches to analyze multi-omics data from preclinical and clinical studies to identify novel drug targets, and to identify and validate biomarkers for patient selection and indication expansion.
- Apply large language models (LLMs), disease- and molecular-level knowledge graphs, and foundation models to integrate diverse data types and drive insight generation.
- Design and apply computational and machine learning methods to analyze, integrate, visualize, and interpret single-cell and spatial transcriptomics, proteomics (e.g., Olink, SomaScan, NULISA, and LC/MS), and metabolomics.
- Integrate and harmonize large-scale human disease data, including pre-clinical and clinical, internal and public 'omics datasets such as UK Biobank, AMP-AD/PD/ALS, and MESA.
- Present scientific reports in internal meetings in all settings and with participants of all levels of the organization, as well as for external audiences.
- Establish partnerships and maintain a collaborative, integrated role with teams to influence the experimental design, assays, data generation, analysis, integration, and interpretation.
- Proactively identify complex obstacles, recommend and implement solutions using a diverse set of resources.
- Work collaboratively with data and quantitative scientists and data engineers to enhance our computational infrastructure and data visualization tools
Education & Experience
- PhD degree in a scientific discipline (or equivalent) with 2+ years relevant experience, or MS with 8+ years relevant experience, or BS with 10+ years relevant experience Prior industry experience with strong background in applying computational biology to research, translational, and/or clinical programs, with a demonstrated ability to meet program objectives and timelines.
Technical Competencies
- Demonstrated experience in large-scale multi-omics and multimodal data integration, network analysis, and meta-analysis.
- Experience applying AI/ML methods to biological or biomedical data
- Statistical analysis experience, including working knowledge of cross-sectional and longitudinal modeling and multivariate data analysis
- Experience in computational method evaluation, development, and implementation.
- Fluency in at least one programming language (e.g., Python or R), with demonstrated experience using libraries for statistical, bioinformatic, and AI/ML analyses.
- Familiarity with high-performance computing (HPC), relational databases (e.g., SQL), and cloud computing platforms (e.g., Amazon Web Services), along with solid knowledge of Unix/Linux environments.
- Strong organizational, collaboration, and commun
Apply for this role
Generate a tailored application kit with a matched cover letter, interview prep, and CV highlights — in under 60 seconds.
Apply Now →Generate Application KitFree account required — sign up in 30s