Summary
The DTU Chemistry department is offering a two-year postdoctoral position focused on developing machine learning methods to combat antimicrobial resistance. The successful candidate will work within an interdisciplinary team to design resistance-proof antibiotics through innovative computational and experimental approaches.
Postdoc in Machine Learning for Combating Antimicrobial Resistance, Kgs. Lyngby, Denmark
Designation
Postdoctoral Researcher
| Attribute | Details |
|---|---|
| Research Area | Machine Learning, Antimicrobial Resistance, Molecular Chemistry |
| Location | Kgs. Lyngby, Denmark |
| Eligibility/Qualification | PhD in Computational Biology/Chemistry or related quantitative field |
| Strong skills in probabilistic modeling and deep learning | |
| Experience with biological/molecular data | |
| Salary and Benefits | Based on collective agreement with the Danish Confederation of Professional Associations |
| Employment Duration | 2 years |
Description
Antimicrobial resistance (AMR) poses a significant threat to global health, leading to millions of deaths annually. This role involves:
- Developing generative protein models to predict resistance variants.
- Designing large-scale DNA libraries for experimental testing.
- Collaborating with chemists and microbiologists to ensure a practical application of models.
- Publishing results and presenting at international conferences.
Candidates should demonstrate a robust publication record and possess a keen interest in interdisciplinary collaboration and innovative problem-solving.
How to Apply
Interested candidates must submit a complete online application, including:
- A cover letter
- CV
- Academic Diplomas (MSc/PhD)
- List of publications
- A representative research sample with a brief explanation of contributions
- Contact information for two references
All materials must be compiled into one PDF file for submission.
Last Date to Apply
Applications must be submitted no later than 31 May 2026 (23:59 Danish time).
For further inquiries, please contact Asst. Prof. Eli N. Weinstein at enawe@dtu.dk.
