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Job DescriptionAre you looking for a patient-focused, innovation-driven company that will inspire you and empower you to shine? Join us as a Associate Director Computational Oncology in our Cambridge office.
At Takeda, we are transforming the pharmaceutical industry through our R&D-driven market leadership and being a values-led company. To do this, we empower our people to realize their potential through life-changing work. Certified as a Global Top Employer, we offer stimulating careers, encourage innovation, and strive for excellence in everything we do. We foster an inclusive, collaborative workplace, in which our global teams are united by an unwavering commitment to deliver Better Health and a Brighter Future to people around the world.
Here, you will be a vital contributor to our inspiring, bold mission.
OBJECTIVES: Takeda is committed to outsmarting cancer so that more patients may have access to our transformational medicines – a robust precision and translational medicine approach thoughtfully and strategically applied in drug development is of critical importance to achieve this important objective of our Oncology Therapeutic Area Unit (OTAU).
The Computational Oncology group within the Precision & Translational Medicine (PTM) function in the Oncology Therapeutic Area Unit (OTAU) at Takeda has the accountability for driving end-to-end computational innovation and excellence from discovery through development, launch, and beyond as needed to advance our pipeline to patients in need. It consists of talented computational biologists who derive actionable scientific insights from large, diverse, and complex biological datasets including clinical trials and external datasets. They partner closely with teams within PTM and across the enterprise, such as Oncology Discovery, the Data Sciences Institute (including Statistics, Global Evidence and Outcomes, Data Architecture), Clinical Pharmacology, Clinical Sciences, as well as with other computational functions at Takeda as needed. Their collaboration guides robust drug target identification and validation, proof-of-concept in the clinic, and the development of pharmacodynamic and predictive markers to inform data-driven decisions. They also propose actionable solutions to be tested in the laboratory and/or the clinic to identify and advance our innovative cancer therapies.
We are seeking an experienced and highly motivated Associate Director of Computational Biology to join our innovative team. The successful candidate will leverage deep learning, multi-omics, spatial biology, single-cell omics, cancer biology, and statistical expertise to drive our drug discovery and development programs. A strong background and understanding of cancer biology with a focus on oncology or immuno-oncology, along with demonstrated experience leveraging computational techniques in the pharmaceutical industry to inform drug discovery and development, will be preferred.
ACCOUNTABILITIES: Develop and implement computational strategies to analyze and integrate multi-omics data, including genomics, transcriptomics, proteomics, and metabolomics.Utilize deep learning and machine learning techniques to uncover novel biological insights, identify therapeutic targets and predict efficacy and safety using molecular data.Drive the analysis and interpretation of spatial biology and single-cell omics data to understand cellular heterogeneity and tissue architecture in the context of disease and response to therapy.Perform robust statistical analysis and data interpretation working closely with statisticians, to support preclinical and clinical studies.Work closely with cross-functional teams, including bioinformaticians, statisticians, biologists, chemists, and clinicians, to advance drug discovery projects.Present findings and recommendations to senior management and stakeholders.Mentor and guide junior scientists and computational biologists within the team.Stay updated with the latest advancements in computational biology and related fields and apply this knowledge to drive innovation.EDUCATION AND EXPERIENCE: Ph.D. in computational biology, bioinformatics, biostatistics, computer science, or similar discipline with 6+ years of experience in pharmaceutical R&D or M.S. with 12+ years of experience or B.S. with 14+ years of experience.Extensive experience with deep learning and machine learning techniques applied to biological data.Proficiency in multi-omics data integration and analysis.Strong background in spatial biology and single-cell omics.Expertise in statistical analysis and data interpretation.In-depth knowledge of cancer biology and its application to drug discovery is a plus.SKILLS: Expertise in high-dimensional 'omic data analysis including but not limited to genomics (Whole Genome Sequencing, Whole Exome Sequencing, single cell genomics, etc.), transcriptomics (bulk RNASeq, scRNASeq, Perturb-Seq, spatial transcriptomics, etc.), epigenomics (ATAC-Seq, ChIP Seq, Bisulfite Seq, etc.), proteomics (MS-based, single cell proteomics, phosphor-proteomics, etc.), metabolomics (MS- and NMR-based), sc-multi-omics, spatial multi-omics etc.Strong understanding of deep learning frameworks and libraries (e.g., TensorFlow, PyTorch, Keras) and experience with machine learning algorithms, neural networks, and model evaluation techniques.Extensive experience with data mining, text mining, systems biology and network analysis.Excellent programming knowledge and experience with cloud computing and command line expertise in R, SQL, Perl, Python and proficiency in Linux environment.Experience with data manipulation and analysis using libraries like Pandas, NumPy, SciPy, and scikit-learn.Familiarity with popular public domain data sources and programmatic interfaces.Familiarity with parallel computing, relational databases and cloud computing or distributed computing.Strong strategic, interpersonal, and influence skills.Ability to work effectively across functions, projects and time zones.Ability to drive multiple priorities forward simultaneously.Excellent communication, presentation, and interpersonal skills.Independent, self-starting and supportive of team-based research and able to work effectively in a matrix organization.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.
LocationsBoston, MA
Worker TypeEmployee
Worker Sub-TypeRegular
Time TypeFull time
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