Postdoctoral Fellow in Machine Learning: The Max Planck Institute for Polymer Research in Mainz, Germany, invites applications for a Postdoctoral Research Fellow position. This role focuses on the project “Correlating Peptide Sequence to Structure and Biological Activity through Machine Learning and Data Mining.” The successful candidate will employ data-mining and machine-learning techniques to identify and predict bioactive peptide sequences that influence cellular responses. If you have a strong background in machine learning, data mining, and a related field, and you’re passionate about exploring the correlation between peptide sequences, structure, and biological activity, we encourage you to apply.
Designation: Postdoctoral Research Fellow
Research Area: Machine Learning, Data Mining, Biological Activity, Peptide Sequences
Location: Max Planck Institute for Polymer Research, Mainz, Germany
Eligibility/Qualification:
- A Ph.D. in Physics, Computer Science, Applied Mathematics, or a related field.
- Proficiency in machine learning, including experience with deep learning frameworks such as TensorFlow or PyTorch.
- Experience with biological data.
- Excellent programming skills in Python or a similar high-level language.
- Evidence of high-quality scientific publications.
- Excellent collaborative and communication skills with an interdisciplinary mindset.
Job Description:
Postdoctoral Research Fellow in Machine Learning and Data Mining for Correlating Peptide Sequence to Biological Activity
As a Postdoctoral Research Fellow, you will work on a cutting-edge project aimed at correlating peptide sequence to structure and biological activity using machine learning and data mining. Your responsibilities will include:
- Utilizing data-mining and machine-learning techniques.
- Identifying and predicting peptide sequences that influence cellular responses.
- Working with high-throughput biological data.
- Collaborating with experts in the field.
- Guiding and accelerating experiments.
- Conducting high-quality scientific research.
How to Apply: Interested candidates are invited to submit the following documents as a single PDF via email:
- Curriculum Vitae.
- List of publications.
- Contact information of two supervisors/collaborators for requesting recommendation letters.
- A brief summary of previous research projects (one or two pages).
Applications will be reviewed starting from 15 November 2023, and will continue until the position is filled. Only shortlisted candidates will be contacted for interviews.
For more information or to apply, please contact Dr. Christopher Synatschke at synatschkecibmpip-mainz.mpg.de.
Disclaimer: This job post is based on information from a reliable source. For additional details about specific conditions and the application procedure, please consult the official website provided in the application details. Ensure that you check the official site for the most up-to-date information and requirements.
