Research Associate (f/m/d)
Deep learning segmentation for biomedical imaging using interactive and active learning

Organisationseinheit

Laboratorium für Applikationen der Synchrotronstrahlung (LAS)

Ihre Aufgaben

We are seeking a highly motivated person (f/m/d) to join our applied deep learning team and contribute to the development of state-of-the-art segmentation methods.

The successful candidate (f/m/d) will have the opportunity to work on cutting-edge research in the field of Deep learning (DL) applied to X-ray Computed Tomography (CT) data.

The goal of the project is to extend existing software and supervised semantic segmentation with interactive and active learning. Semantic image segmentation is a labor-intensive and time-consuming task that requires manual annotation by experts. Therefore, the use of interactive and active learning methods can significantly reduce the amount of manual annotation. Interactive learning involves human interaction with the learning algorithm, where the user provides feedback to the DL model to improve its performance. The user can review the annotations and correct any errors, which can be used to retrain the model and improve its accuracy. Active learning involves selecting the most informative samples from a large pool of unannotated data to maximize the learning efficiency. Combining interactive and active learning methods can further enhance the efficiency of semantic image segmentation.

Your tasks within the project:

• Review state-of-the-art approaches for interactive and active learning
• Implement the selected approaches
• Integrate the devised models into the segmentation software and workflows

Eintrittstermin

as soon as possible

Ihre Qualifikation

We are looking for a candidate (f/m/d) with a strong scientific background and a passion for using AI technology to advance the biomedical field. If you have a PhD or Master's degree in Computer Science, Computer Vision, Machine Learning, or a related field; have a strong understanding of deep learning principles; interested to contribute to various applied projects in the field of biomedical imaging - we would like to hear from you.

They shall have:

• Master in computer science, mathematics or engineering
• In-depth understanding of the Deep Learning principles
• Good programming skills: Python, Git, OOP, and DL framework of choice are a must
• Experience with image processing and computer vision
• Track record of DL related publications is a plus
• Confidence in English

Salary

Salary category 13, depending on the fulfillment of professional and personal requirements.