Postdoctoral Associate | Laboratory of Computational Molecular Discovery

Organization Overview

The Lyu laboratory is particularly interested in molecular docking, a structure-based virtual screening method that can be used to evaluate virtual libraries of great size and diversity, followed by selection of the best-fitting molecules for synthesis and testing. With the recent availability of "make-on-demand" virtual libraries containing billions of molecules, there is a vast potential for ligand discovery. The lab is working on innovative approaches to leverage this expansive chemical space for structure-based drug design and to gain a deeper understanding of how structure and chemical space expansion can be utilized to create chemical tools for studying biology.

Overview

We are seeking enthusiastic and dedicated postdocs to join our dynamic and growing lab. If you are passionate about computer-aided drug design, we invite you to become a part of our team. Our lab values collaboration, mentorship, diversity, and fun, and we strive to foster a positive culture within our scientific endeavors.

Our current research priorities include:

1. Developing new molecular docking algorithms
2. Test these new algorithms on underexplored targets with potential therapeutic values
3. Developing computational tools for the generation of new chemogenetic tools to study various biology

We welcome new ideas from our team members. If you are ready to take the next step in your scientific career and make a meaningful impact in the field, apply now to join us in our mission to push the boundaries of research. More research can be found https://lyulab.org/research/

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

Qualifications

REQUIRED QUALIFICATIONS:

• 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

The Rockefeller University is an equal opportunity employer - veterans/individuals with disabilities. Qualified applicants will receive consideration for employment without regard to characteristics protected by applicable local, state or federal law, including but not limited to disability and protected veteran status.

The salary of the finalist selected for this role will be set based on various factors, including but not limited to organizational budgets, qualifications, experience, education, licenses, specialty, and training. The hiring range provided represents The Rockefeller University's good faith and reasonable estimate of the range of possible compensation at the time of posting.