Position:
Post-doctoral fellows and Ph.D. students for the Molecular Modeling and
 Computer-Aided Drug Design (CADD) field

Location:
Prof. Sun Choi, Ph.D. 
Director, Global AI Drug Discovery Center
College of Pharmacy & Graduate School of Pharmaceutical Sciences, 
Ewha Womans University 
52, Ewhayeodae-gil, Seodaemun-gu, Seoul 03760, Korea
Tel: +82-2-3277-4503 
Fax: +82-2-3277-2851 
E-mail: sunchoi-,-ewha.ac.kr 
Homepage: http://caddsc.ewha.ac.kr/ 

Description:
Ewha Womans University (http://www.ewha.ac.kr/mbs/ewhaen/index.jsp) is one
of the most prestigious universities in South Korea. Ewha has continued to
evolve throughout its more than 130-year history and now, it became the
largest women's university in the world with 25,000 enrolled students. The
College of Pharmacy in Ewha is the oldest and largest school of pharmacy
in Korea with a history of more than seventy years of Pharmacy education.
Moreover, only the top 1% of excellent students in Korea enter the College
of Pharmacy, and our graduates now number over 10,000.

In the laboratory of molecular modeling and drug design (Prof. Sun Choi;
http://caddsc.ewha.ac.kr/), various technology and methodology of CADD,
cheminformatics, computational medicinal chemistry and biomolecular
simulations are studied. Using computational methods, we develop strategies
for drug discovery involving cancer, virus, cardiovascular disease,
osteoporosis, etc. Adapting to the target systems, various studies are in
progress, including docking and binding mode analysis, active site and
pharmacophore analysis, structure-activity relationships study and
activity/property/toxicity prediction, chemical library and molecular
design (target structure-/ligand-based), HTS data analysis, hit/lead
optimization, study of molecular interactions and mechanisms, and big data
and artificial intelligence (AI)-based drug discovery. Based on the
high-quality and extensive research outcomes, we are continuously
publishing articles in world-renowned journals, such as Journal of the
American Chemical Society, Cell Metabolism, Angewandte Chemie, Journal of
Medicinal Chemistry, and Theranostics. Our laboratory was selected as the
National Leading Research Laboratory (NLRL) funded by the Korean government,
and has engaged in active research activities, leading the Global AI Drug
Discovery Center.

  * Research Areas
   - Computer-Aided Drug Design (CADD) Methods and Applications, including
     Docking,
     Pharmacophore Modeling, Homology Modeling, etc.
   - Protein-Ligand Interaction & their Mechanism of Action Studies 
   - Molecular Design, Combinatorial Library Design, Virtual Screening 
   - Drug Discovery Research for Various Diseases in Cell Signaling
   - Biomolecular Simulations: Protein Motion and Allostery
   - Theoretical Studies of Enzymatic & Chemical Reactions
   - Big Data Analysis and Artificial Intelligence (AI)-based Drug
     Discovery
	
  * Required Qualifications for the Post-doctoral Position:
   - Ph.D. in medicinal chemistry, theoretical/computational chemistry,
     structural biology, bioinformatics, biochemistry or related disciplines
   - *Established record of high-quality scientific research and
      publications in high impact journals
   - Experiences in the fields of QM/MM calculations, MD simulations
     (including enhanced sampling techniques), molecular modeling,
     Computer-Aided Drug Design (CADD), and/or Artificial Intelligence (AI)
     are preferable
   - Ability to work both independently and as a member of a collaborative,
     scientific team
   - Excellent verbal and written communication skills in English

*Selected eligible candidates will also have the opportunity to apply for a
 Korean Government grants covering a program period of 3~5 years.
- Brain Pool (BP, BP+) Program for inviting outstanding scientists from
  overseas

To apply:
  - Send an email to sunchoi-,-ewha.ac.kr with the following application list.
    1. Cover letter (describing your research interests and interest in our group)
    2. CV, including publication list
    3. Contact information for 3+ references