FAQs
What is the application deadline for this position?
The application deadline is February 28, 2025.
What qualifications are required for this position?
A Master's or PhD in Computer Science, Mathematics, or a related field is required, along with a strong foundation in machine learning, computer vision, or medical image analysis.
Are teaching responsibilities included in the role?
Yes, the position includes teaching responsibilities, which may involve up to 5 semester weekly hours (SWS), depending on co-funding.
Is prior experience in medical image analysis necessary?
While a strong foundation in machine learning, computer vision, or medical image analysis is essential, specific prior experience in medical image analysis is not explicitly required.
What programming languages should applicants be familiar with?
Applicants should have proven programming skills in Python, and familiarity with tools like R and Unix shell scripting is also beneficial.
What type of research work is expected in this role?
The position involves conducting world-class research in deep learning for medical image analysis, presenting and publishing results at top-tier conferences and journals, and actively contributing to the lab's research mission.
Are there opportunities for career advancement in this position?
Yes, the position supports further scientific qualification, such as a PhD or Habilitation, and there are secure options for future contract extensions.
Does the lab support collaboration with other institutions?
Yes, the lab collaborates with world-class partners at institutions like Stanford, MIT, Imperial College London, and NYU, providing opportunities for extended research stays.
What is the salary for this position?
The salary is competitive and aligned with TV-L regulations, approximately €55,000 per year.
Is there a commitment to diversity and inclusion in the hiring process?
Yes, FAU is committed to equality and diversity, and applications from underrepresented groups, including women, minorities, and individuals with disabilities, are highly encouraged.