Postdoctoral Fellow: Rethinking drug design with deep learning, Sweden

Study in Sweden

Postdoctoral Fellow: Rethinking drug design: AstraZeneca is looking for a highly motivated Postdoctoral Fellow to join their Molecular AI department to conduct innovative research using deep learning methodologies for drug design. The successful candidate will be working with a team of experts from diverse backgrounds and a world-class academic mentor. The project will involve developing deep learning architectures for molecular optimization, synthesis prediction, and property prediction.

  • Location: Gothenburg, Västra Götaland County, Sweden
  • Designation: Postdoctoral Fellow
  • Research Area: Drug design using deep learning
  • Job ID: R-149536
  • Date Posted: 09/03/2023

Main Duties & Responsibilities:

  • Research, design and implement innovative deep learning methodologies for drug design
  • Plan, write, publish and present high-quality scientific papers
  • Opportunity to mentor PhD students, graduate scientists, and master thesis students

Qualification, Skills & Experience:

  • A PhD or equivalent in cheminformatics, computer science or a related field
  • Proven experience with deep learning
  • Excellent written and verbal communication skills
  • Programming expertise, preferably in using Python
  • Ability to conduct independent and innovative research

Desirable Requirements:

  • Familiar with Transformer-based language models
  • Basic knowledge of cheminformatics
  • Experience with deep learning frameworks, e.g., PyTorch and modern neural network architectures
  • Awareness of recent development in the field of deep learning

Location: The position is located at AstraZeneca’s research site in Goth

enburg, Sweden.

How to Apply: To apply for this position, please submit your application along with your CV, a cover letter highlighting your skills and experience relevant to this role, and contact details of two referees.

Last Date for Apply: Advert Opens: March 10th 2023 Advert Closes: April 16th 2023




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