Pfizer Medicine Design focuses on small molecule drug discovery efforts in multiple disease areas. Our location in Cambridge, MA is at the center of biomedical innovation, facilitating collaborations with local universities and biotech companies. We are seeking a talented computational chemist to impact drug discovery projects by applying computational techniques to accelerate the discovery of revolutionary medicines and create a healthier world for everyone.
The successful candidate will generate and evaluate hypotheses to assist design decisions and influence project direction by deploying and/or developing computational methods and workflows. As an integral member of Medicinal Chemistry teams, you will support all aspects of small molecule drug discovery, ranging from hit identification to lead optimization to candidate selection. This is an opportunity to directly contribute to the discovery of medicines for cardiovascular and metabolic diseases, antivirals, and other emerging medical needs by applying computational chemistry techniques on teams with experienced multidisciplinary drug hunters. ROLE RESPONSIBILITIES
As an independent researcher and integral member of project teams, you will use your experience and knowledge to determine appropriate computational chemistry techniques to drive projects forward. The position involves the application of a wide variety of computational approaches including HTS analyses, lead identification, structure-based drug design, ligand-based design, pharmacophore modeling, QSAR and in silico modeling of ADME/Tox to generate and evaluate hypotheses to influence design decisions. The candidate is also expected to develop novel computational approaches or workflows to solve specific or general problems in drug discovery. BASIC QUALIFICATIONS
- Ph.D. in Computational Chemistry or a related discipline
- Strong understanding of computational chemistry and physical chemistry principles
- Knowledge in one or more areas of the computational chemistry discipline, such as molecular dynamics and structure-based design, ligand-based design, quantum mechanics, QSAR, homology modeling or pharmacophore modeling
- Demonstrated problem solving abilities and good communication/organizational skills within a collaborative team environment
- Experience in one or more modeling software packages, i.e. Schrodinger Maestro, CCG MOE, OpenEye toolktis, etc
- Working knowledge of Linux environment and practical experience in one or more programming and scripting languages such as Shells, Python, R, Jupyter, etc.
- Basic knowledge of statistics and machine learning algorithm and techniques.
- Experience in manipulating chemical structure data, molecular properties, etc.
- Good knowledge of target families of therapeutic interest, such as GPCRs or Kinase.
- 1-3 years of PostDoc or industrial experience
- Relocation support available
- Employee Referral Eligible
- Work Location Assignment:On Premise
- Last Day to Apply: 2/5/2022
Relocation assistance may be available based on business needs and/or eligibility.
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Research and Development