About us:

This unique opportunity is a joint position between the Data Science Group of the Department of Statistics of the Ludwig-Maximilians-Universität (LMU) Munich, Machine Learning Consulting Unit of the Munich Center for Machine Learning (MCML) and the Junior research group MIDorAI of the Medical Informatics Initiative (MII) at Department of Biomedical Informatics, Medical Faculty Mannheim (MedMa), University of Heidelberg (UHD).

We are looking for you:

PhD Position in Generative Models for Multimodal Patient Data in Neuroradiology (m/f/x)

in Munich

Your tasks and responsibilities:

Background: Due to advances in data collection and storage, patient data has become more and more complex and multimodal (tabular, text, images) over the years. Yet, often parts of the data are missing or not available in sufficient quantities, especially for some of the modalities and for specific purposes (e.g. image data for computer vision applications).
With the advance of generative models, generation of synthetic data (digital twin) has come into research focus. This allows the creation of synthetic, yet realistic, data that can be used for downstream applications like training and evaluation of prediction models.
We are seeking highly motivated PhD candidates with a passion for bioinformatics, machine learning, and deep learning to contribute to a cutting-edge project in AI research and clinical neuroscience.

Project focus: This project revolves around generative models and the integration of multimodal tabular data, text, and imaging in the realm of neuroradiology. You will have the opportunity to develop and apply state-of-the-art computational models to unravel insights that hold immense potential for clinical applications.

Exemplary Research Questions:

• Investigate and develop extensions of diffusion models to generate, e.g. synthetic 3D imaging data of stroke, brain tumor and dementia patients
• Develop new few-shot learning & few-shot prompting approaches
• Develop new classification and segmentation and image captioning approaches and compare to baselines such as UNet, VNet, nnUNet, etc.

Your qualifications:

• Master degree in a relevant field (Statistics, Machine Learning, Data Science, Computer Science, Bioinformatics, etc.)
• Very good academic performance
• Very good coding skills in Python (R knowledge beneficial)
• Experience with Deep Learning, particularly computer vision (ideally 3D data), segmentation, etc.
• Familiarity with different Deep Learning frameworks (e.g. Keras, Pytorch, Tensorflow)
• Self-sufficient and organized working style
• Ability to communicate and work in a team

Benefits:

Join our team at the forefront of cutting-edge research! This is a unique opportunity to be affiliated with top-ranked universities LMU Munich and Medical Faculty Mannheim, University of Heidelberg. Your PhD project will be in the realm of generative AI motivated by applied research in neuroradiology. Financing is divided equally between the partnering universities. The primary location of work will be in Munich with regular exchange and visits to Mannheim. Working hours are flexible and it’s possible to conduct part of the work from home office. You will obtain a Degree as Dr. rer. nat. from LMU Munich.

In Munich, you will be part of the Data Science Group as well as the Machine Learning Consulting Unit with offices in central Munich. You will also be affiliated with the Munich Center for Machine Learning (MCML), one of the six AI centers in Germany. As such, you will be part of a vibrant and growing community with the possibility to meet and exchange with the top AI researchers in and around Munich. You will also enroll in the doctoral program of the MCML. Besides your main research, you will consult applied scientists from other departments of the LMU on the use and deployment of Deep Learning models. Within your group, you will have the opportunity to join various research focus groups that meet regularly to exchange research.

Also possible in a part-time capacity.

Contact:

Please upload your application as one single PDF file here (PW: genAI24)
The Application should include a motivational letter, a CV, academic transcripts, relevant certificates as well as other supporting materials like reference letters (including contact to academic referee), list of publications, links to working samples, certificates, and further relevant documents.

Applications should be uploaded via the link above. If you have any other question before application, please sent an e-mail to Andreas Bender with subject line "PhD Position Generative Models for Multimodal Patient Data in Neuroradiology".

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