Postdoctoral Associate
The Rockefeller University
This job at a glance
- Who can apply
- New grads and up to 2 years
- Must know
- Data structures & algorithmsMachine learningPythonLinux
- Nice to have
- Deep learningPyTorchTensorFlow
- Work
- On-site in New York
- Pay
- Not stated by the employer.
- Skill demand
- Machine learning31%Python30%Data structures & algorithms10%Linux5%of 100 similar entry-level jobs posted in the US this week
- Listed
- Nov 12, 2026 · still open
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About the Role
The Lyu laboratory is focused on molecular docking, a structure-based virtual screening method for evaluating large virtual libraries and selecting molecules for synthesis and testing. The lab aims to leverage expansive chemical space for structure-based drug design and to understand how structure and chemical space expansion can create chemical tools for studying biology. We are seeking enthusiastic and dedicated postdocs passionate about computer-aided drug design.
Current Research Priorities
- Developing new molecular docking algorithms
- Testing new algorithms on underexplored targets with potential therapeutic values
- Developing computational tools for generating new chemogenetic tools to study various biology
Responsibilities
- Drive independent and collaborative research projects
- Develop methods and approaches appropriate to the research questions
- Lead and contribute to the preparation of manuscripts for publication in peer-reviewed journals
- Present research findings at lab meetings, campus seminars, and scientific conferences
- Contribute to grant writing and funding efforts
- Mentor trainees as appropriate
Requirements & Tech Stack
- PhD in computational chemistry, computer-aided drug design, cheminformatics, chemical engineering, structural biology or a closely related field.
- Demonstrated research experience in computer-aided drug design, including proficiency with one or more of the following:
- molecular docking
- AlphaFold-like structural prediction
- structure-based or ligand-based virtual screening
- free energy calculations
- machine learning methods applied to drug discovery
- Strong programming skills: Python required.
- Familiarity with shell scripting and HPC/Linux environments expected.
- Ability to work independently, design and execute research projects, and communicate scientific findings effectively in written and oral form.
Preferred Qualifications
- At least one first-author publication from PhD work in a peer-reviewed journal.
- Experience with large-scale virtual screening of make-on-demand or ultra-large chemical libraries.
- Familiarity with generative models for molecular design, deep learning frameworks (PyTorch or TensorFlow), or cheminformatics toolkits (RDKit, OpenEye).
- Prior experience collaborating with experimental medicinal chemists or structural biologists.