About the Position

You will work on developing new methodologies to analyze molecular structures, such as proteins, and contribute to understanding molecular complexities in 3D. The position provides an excellent opportunity to engage in national and international collaborations and contribute to groundbreaking projects that integrate AlphaFold, high-performance computing, and innovative machine learning approaches.

Key Responsibilities

• Utilize machine learning and feature engineering to design novel methods for understanding molecular structures.
• Extend existing methods to analyze molecular structure ensembles and averages, incorporating computer vision techniques for unsolved biological problems.
• Develop and implement high-performance computing solutions using Sweden’s super-computing infrastructure.
• Collaborate with national and international teams for software development and applied biological research.
• Participate in teaching or other departmental duties (up to 20% of full-time).

Eligibility Requirements

Applicants should have:

• A Master’s degree (or equivalent) in computational/mathematical fields or demonstrated experience in structural biology or bioinformatics.
• Proficiency in Python and C++, with experience in collaborative software development using version control tools like Git.
• Skills or experience in data visualization, clustering, classification, deep learning, or molecular dynamics.
• Familiarity with large-scale data analysis and UNIX environments.
• Excellent oral and written communication skills in English.
• Knowledge of macromolecular structure analysis, such as cryo-EM, crystallography, or molecular dynamics, is beneficial but not mandatory.

What We Offer

• Duration: Four years of full-time equivalent PhD studies (potentially extendable up to five years based on teaching duties).
• Salary: Competitive salary based on locally negotiated progression scales for PhD students.
• Access to state-of-the-art facilities, including the Berzelius super-computing infrastructure and the SciLifeLab national cryo-EM microscopy facility.
• Opportunities for national and international collaborations, including partnerships with the Chan-Zuckerberg Imaging Institute and the University of Oxford.
• A vibrant research environment with cross-disciplinary collaborations in bioinformatics, statistics, and machine learning.

Application Process

To apply, click the “Apply” button on the official job portal and submit the following documents by 20th December 2024:

1. A motivation letter explaining your interest in the role and relevant skills.
2. Your CV, including evidence of experience (e.g., GitHub contributions).
3. Transcripts of your Bachelor’s and Master’s degrees.
4. Additional documents showcasing your qualifications (optional).