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 TakedasPrivacy 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 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 to bring life-changing therapies to patients worldwide. Objective / Purpose: This role will play a pivotal role in discovering first-/best-in-class small molecules, bifunctional degraders, and RNA/oligonucleotides by leveraging computational chemistry and cheminformatics methods to design molecules as well as providing scientific mentoring and leadership to junior members of the team. The person will be tightly integrated into the computational chemistry team and also provide timely and innovative designs and support to our drug discovery programs. Additionally, the role will collaborate closely with global chemistry, structural biology, DMPK, and safety experts for molecular design and help to define a roadmap for computational tools that empower medicinal chemists in their design efforts. While the role will focus on a specific set of programs at any point in time, the drug discovery programs span Takedas therapeutic areas, including oncology, neuroscience, gastroenterology, and inflammation. Accountabilities: Co-design molecules for several drug discovery programs across various modalities including small molecules, molecular glues, degraders, and RNA/oligonucleotides Demonstrate expert understanding of computational chemistry principles and their application within a multidisciplinary drug discovery environment Provide crucial technical knowledge and input to project teams to drive decision-making in drug discovery projects by applying in-depth knowledge of structure-activity relationships (SAR), target biology, and predictive methods for assessing on- and off-target activity, physical properties, pharmacokinetics / pharmacodynamics (PK/PD), and synthetic feasibility Implement and execute innovative computational methodologies and tools such as AI-based drug discovery, state-of-the-art commercial and open-source software tools/methods Mentor junior computational chemists on molecular design best practices Open to traveling and spending time on both sites as required Serve as a trusted thought partner, helping to drive ideation and execution of innovative chemistry strategies that meet Takedas therapeutic goals Education & Competencies (Technical and Behavioral): The ideal candidate will have demonstrated experience impacting drug discovery exemplified by delivering molecules to the clinic, leveraging cutting-edge physics-based modeling, AI/ML-driven approaches, and generative chemistry, collaborating effectively with biologists, structural biologist, pharmacologists, DMPK scientists as well as leading and mentoring computational chemistry teams. PhD in Computational Chemistry, Chemical Physics, Medicinal Chemistry, or related disciplines, with 20+ years of experience in pharmaceutical or biotech Deep expertise in structure-based design, ligand-based design, and cheminformatics with a strong background in medicinal chemistry principles Proven track record in using computational methods to drive small molecule drug discovery, from hit identification to clinical candidate selection Extensive knowledge of computational chemistry tools, including docking, molecular dynamics, FEP, QSAR modeling, and generative AI Strong programming and scripting skills (e.g., Python, R, C/C++) with experience in building and automating computational workflows Strong publication record demonstrating innovative contributions to computational chemistry and drug discovery
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