Sr. Scientist, Neuroscience Computational Biology

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.

• 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, Soma Scan, 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

• 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.

• 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 communication skills, with the ability to clearly convey complex scientific concepts and influence multidisciplinary teams.

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