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Postdoc Research Fellow

vor 1 Monat


Frankfurt am Main, Deutschland Universitätsklinikum Frankfurt Vollzeit

**"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 7,500 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.

**PostDoc Research Fellow / Research Scientist - Machine Learning / Oncology**:
(We are targeting applicants of all genders)
Full time | initially limited to 3 years | Announcement number: 136-2023

We are seeking a motivated **PostDoctoral Research Scientist / Fellow** to join our team at the** **Buettner Lab** in **Medical Clinic 2** starting from the earliest possible date. The Buettner lab works on the intersection of machine learning and oncology and as such is actively pursuing original research in both areas. Our research focuses on (computational) genomic medicine and trustworthy machine learning, with regular publications in high-impact venues such as Cancer Cell, Nature Methods, Cell, NeurIPS, AAAI, CVPR. The lab is part of the German Cancer Consortium (DKTK), the German Cancer Research Center (DKFZ) and Goethe University Frankfurt. It is located at the university hospital UCT Frankfurt-Marburg. The position is initially limited to one year with the option of an extention to 3 years (funding available).

**YOUR ROLE**:

- Your research will explore how trustworthy machine learning solutions can be developed in a federated environment with continual learning strategies
- You will work as part of a large international consortium with collaboration partners across industry and academia, with regular consortium meetings across Germany and Austria
- You will work closely with clinicians and explore how those solutions can be used to analyse data from cancer patients in a trustworthy manner

**WHO YOU ARE**:

- An excellent knowledge of machine learning methods and statistics is essential.
- At least 2 years experience on research to machine learning is desired.
- Experience with federated learning, continual / life-long learning and/or uncertainty qualification is a plus.
- Very good knowledge of python and best practices in software development as well as experience with Linux environments are required.
- Due to legal regulations, a valid proof of measles immunity / measles vaccination is required.

**WHAT WE OFFER**:

- **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 (more information can be found here), 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

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 February, 26th 2023 to apply. Please state the announcement number, a possible starting time and your salary expectations. For further information, please contact Prof. Dr. Florian Büttner (+49 69 6301 86212).


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