"Knowledge becomes health" - we are filling this motto with life every day, developing new ideas and improv-ing old-established knowledge. The University Hospital Frankfurt has existed since 1914. Our around 8,500 employees contribute with their skills and knowledge to the 33 specialist clinics, theoretical clinical institutes, and administrative departments. The close connection of health care with research and teaching, as well as a climate of collegiality, internationality, and cross-professional cooperation characterize the university hospital.

PhD – Machine Learning

(We are targeting applicants of all genders)
Full time | limited to 3 years with possibility of extension | Announcement number: 987-2024

The Edinger Institute is a German research institution and neuropathological diagnostic section at the University Hospital Frankfurt am Main. We are part of an excellent scientific community in Frankfurt including the Mildred Scheel Career Center (MSNZ), the Univeristy Cancer Center (UCT Frankfurt-Marburg), the German Consortium for Translational Cancer Research (DKTK) and the Frankfurt Cancer Institute (FCI). The Biobank and Immunomonitoring-Platform of the FCI is located at the Edinger Institute and offer optimal conditions for tissue-based research. The AG Molecular and Computational Neuropathology uses machine and deep learning as well as genome-wide molecular analysis methods in tumor specimens and liquid biopsies to develop new diagnostic tools and to establish novel prognostic and predictive biomarkers for neurooncological patients.

 

About the project
We are recruting a PhD student for a DFG-funded research project focused on the automated detection and classification of tumor cells in cerebrospinal fluid samples by deep learning models. The aim is to develop a fully digital workflow and clinical-grade deep learning tool to tranform the current practice in neuropathological institutes of manual cell differentiation and counting of cerebrospinal fluid samples using a microscope. The thesis will build on a previously published algorithm (PMID: 36519297; https://github.com/pseegerer/csf_cell_classification) and use a new, multicentric, well-annotated cancer cell dataset to improve automated cell segmentation, cancer cell detection and tumor origin prediction.

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Your role

  • Data preparation and training of convolutional neural networks to improve cancer cell detection and origin prediction
  • Comparison and selection of cell segmentation algorithms and optimization for cerebrospinal fluid samples
  • Development of interactive visualization and reporting tools for diagnostics and collaborative research projects
  • Implementation of explainable AI methods and confidence scores to increase the interpretability of classification results for diagnostic use
  • Establishment of a diagnostic workflow for deep learning-based cerebrospinal fluid cell analysis for a clinical evaluation period (12 months) in parallel to routine diagnostics

Who you are

  • You have successfully completed a Master’s degree in a related field such as bioinfromatics, computer science or physics and are pursuing a publication-based doctorate.
  • Proven programming experience in languages such as Python, R, or C++, frameworks such as PyTorch, TensorFlow, or NumPy, and version control systems like Git
  • Excellent communication skills and ability to collaborate
  • Proficiency in English, good knowledge of German (min. B2)
  • Due to legal regulations, valid proof of measles immunity / measles vaccination is required

What we offer

  • Work environment: Working in an interdisciplinary, young research team.
  • Collective agreement: In addition to an attractive salary based on a collective agreement with an annual special payment, you benefit from long-term security through company pension schemes
  • Mobility: Free public transport in all Hessen (Free State Ticket Hessen)
  • Campus: Our attractive university hospital campus offers a modern cafeteria, various cafes, and opportunities to rest in numerous green spaces. A walk on the riverside of the Main offers relaxation during breaks
  • Work-Life-Balance: Part-time employment is possible, we offer childcare in our daycare center (if you have any questions, please contact UKF-Familienservice), child care during holidays
  • Health Promotion: Benefit from our attractive health offers. We offer regular online and face-to-face courses on nutrition, relaxation, sports and exercise.
  • Professional development: Internal and external training for your professional development
  • Any questions? Many answers can be found in our FAQs for new employees. If you have any further questions, please do not hesitate to contact us.

Women are underrepresented in these positions at the University Hospital Frankfurt. Applications from women are therefore particularly welcome. Disabled applicants are preferred if they have the same personal and professional qualifications.

Join our team

Use the time until January 06, 2025 to apply. Please submit your online application including a possible starting date and your salary expectations. For further information regarding the position and project, please contact PD Dr. Leonille Schweizer via 069 / 6301 84169 or via leonille.schweizer@med.uni-frankfurt.de.

Apply now

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