From: jobs at ccl.net (do not send your application there!!!)
To: jobs at ccl.net
Date: Thu Jul 2 10:19:45 2026
Subject: 26.07.02 Postdoc, AIDD and CADD, Beijing, China
Postdoctoral Fellowships: AIDD/CADD

Lab: Dr. Fan's Lab (www.cimrbj.ac.cn/en/channel/2013512987888979968.html)

Position Type: Full-time Postdoctoral Researcher (Multiple Openings)

The Chinese Institutes for Medical Research (CIMR) is a pioneering, 
flagship research institute in Beijing, integrating cutting-edge 
fundamental science with clinical translation across a network of top-tier
medical centers.

The Fan's Lab at CIMR (Beijing) integrates advanced machine learning with
high-precision physical simulations to accelerate molecular therapeutics 
and enzyme engineering. Our research focuses on the molecular mechanisms, 
allosteric regulation, and ligand spaces of high-value targets (including
GPCRs, transporters, and kinases) and the rational design of functional 
biocatalysts (e.g., fluorinases).

Our group is primarily computational, but uniquely operates an internal 
wetlab for rapid experimental validation, alongside a premium network of 
clinical and pharmaceutical collaborators. The PI has a proven track record
of top-tier publications (Science Advances, Nat Comm, PNAS, ACS Catalysis) 
and global patent applications. We are seeking two outstanding Postdoctoral 
Researchers to lead separate, complementary tracks:

Track A: AI-Driven Drug Discovery (AIDD) Specialist

Role & Project Focus:
You will work on deep learning and machine learning method development to
accelerate drug discovery pipelines. Working directly at the dry/wet-lab 
interface, you will define actionable modeling questions, prioritize 
compounds, and iterate through design-test-analyze cycles. Initial work 
focuses on hit discovery, multi-target modeling, and chemical space 
optimization across multiple therapeutic areas.

Qualifications:
1) Ph.D. in Machine Learning, Computer Science, Computational Chemistry, 
Cheminformatics, Bioinformatics, or a related quantitative discipline.
2) Strong track record in ML development (peer-reviewed publications or 
substantial open-source software contributions).
3) Expertise in deep learning workflows for molecular/target modeling 
(e.g., GNNs, diffusion, contrastive learning) or large-scale data curation
and virtual screening pipelines.
4) Robust software engineering practices (Linux, PyTorch/TensorFlow).
5) Excellent scientific communication skills in English.


Track B: Computer-Aided Drug Development (CADD) Specialist

Role & Project Focus:
You will work on the development and application of structure-based, 
physics-driven methodologies to decipher protein-ligand interactions and 
map molecular mechanisms at superfamily and genome scales. You will 
investigate structural dynamics, activation pathways, and drug-resistance
phenotypes of GPCRs, transporters, and kinases, as well as drive in silico
enzyme engineering.

Qualifications:
1) Ph.D. in Computational Biology, Computational Chemistry, Biophysics, 
Pharmaceutical Sciences, or a related field.
2) Hands-on expertise in advanced computational structural biology methods,
including protein structure prediction/modeling, structure-based virtual 
screening, molecular docking, and advanced molecular dynamics (MD) 
simulations (unbiased and enhanced sampling)
3) Strong programming/scripting proficiency (Python, C/C++, Fortran, or
Perl) and familiarity with standard simulation suites (e.g., GROMACS,
MODELLER, DOCK, Schrodinger).
4) Excellent scientific communication skills in English.
Please submit your Cover Letter, a detailed CV (including publication and 
GitHub links), and contact info for 2-3 references in English to 
fanhao^^cimrbj.ac.cn
Review of applications will begin immediately and continue until the 
positions are filled. Start dates are flexible.
NOTE THAT E-MAIL ADDRESSES HAVE BEEN MODIFIED!!!
All @ signs were changed to ^^ to fight spam. Before you send e-mail, you need to change ^^ to @
For example: change joe^^big123comp.com to joe@big123comp.com
Please let your prospective employer know that you learned about the job from the Computational Chemistry List Job Listing at https://server.ccl.net/jobs. If you are not interested in this particular position yourself, pass it to someone who might be -- some day they may return the favor.