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3 job vacancies
in the categories
Biophysics Bioinformatics Mathematics Computer Sciences Postdoc North Rhine-Westphalia University Hospital

  • Postdoc (f/m/d) for machine learning in computational digital pathology

    2022-04-19 Universitätsklinikum der RWTH Aachen Aachen Postdoc (f/m/d) for machine learning in computational digital pathology - Universitätsklinikum der RWTH Aachen - Logo
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Postdoc (f/m/d) for machine learning in computational digital pathology

Published
2022-04-19
Application deadline
2022-06-13
Full-time position
Universitätsklinikum der RWTH Aachen
Aachen
Universitätsklinikum Aachen - Logo
pic
The Institute of Pathology is offering a new position for a

Postdoc (m/w/d) for machine learning in computational
digital pathology

The full time position (38,5 hrs/week) is initially for 3 years. A prolongation is desired. Home office is possible according to our service agreement.
We are a young team of biologists, medical doctors (nephrologists and pathologists), AI-developers, computational biologists and data scientists working on basic and translational research with particular focus on kidney diseases. Both large clinical and preclinical datasets are already available. We are strongly team-oriented and an internationally well-established and connected teams. We offer a broad spectrum of well-established and available methods and available SOTA infrastructure ranging from wet-lab till directly available IT and computation resources. We are also constantly developing novel methods and are open to new approaches.
We are looking for:
an independent researcher with a strong focus and interest in machine learning and statistical analysis of large-scale pathomics data. Our team has developed a deep learning pipeline for characterization of anatomical features in histology slides. This allow us to characterize the already available large cohorts of pathology slides from patients with kidney diseases as a major use case. The candidate will focus on development of novel methods and approaches to analyze, visualize and interpret large-scale pathomics data and relate these to clinical information of patients This highly dynamic and exciting project is embedded within an environment of state-of-the-art AI development, technological infrastructure, direct clinical and translational medical research and computational biostatistics with strong international network. The project is interdisciplinary in close cooperation between the groups of Prof. Boor (clinical and digital pathology & AI development) and Prof. Costa (computational genomics) and embedded within the ERC consolidator grant (AIM.imaging.CKD) and the Clinical Research Unit 5011 (InteraKD – Integrating emerging methods to advance translational kidney research) but also the large national consortia focusing on COVID-19 autopsies (www.DeRegCOVID.ukaachen.de and www.netzwerk-universitaetsmedizin.de/projekte/defeat-pandemics#c508).
The ideal candidate will require:
  • Ph.D. in data science, bioinformatics, biostatistics, biophysics, mathematics, or related field
  • A solid track of academic record in machine learning and/or image analysis
  • Demonstrated experience in data analysis with Python, R and high-performance computing
  • A strong background in and passion for data integration, data and knowledge management, biological interpretation
  • High level of methodological and scientific independence
  • Enthusiasm for multidisciplinary research
  • Excellent proficiency in written and oral communication skills in English (Level C2)
  • Strong interest in Teamwork
Why should you choose us?
  • We offer unparalleled variety - 300 professions under one roof
  • We offer performance-based remuneration in accordance with the provisions of TV-L (EG13), including attractive public service benefits
  • In addition to a wide range of further education and training opportunities, we offer you a wide range of health promotion options as well as the extensive university sports program
  • Monthly employee discounts through our corporate benefits program to save on private shopping
  • Flexible working hours so that you can better combine work and private life; because your work-life balance is important to us
  • Attractive conditions for local public transport or discounted employee parking; so that you have a relaxed commute
  • We have a wonderful company kindergarden; so that your children are always close by
This position is not gender specific.
The RWTH Aachen University Hospital promotes equal opportunities and diversity. Applications from women are expressly encouraged and if the applicant is suitable qualified, they will be given priority in accordance with the LGG. If suitably qualified, people with a registered disability will also receive priority.
Employment at less than full time is negetiable.
Please note that taking up this role can only occur after a pre-employment health check has confirmed evidence of immunisation (for example evidence of immunity according to paragraph 20, section 3 of the infection prevention law (vaccination for COVID-19).
You should preferably use our digital application portal at www.karriere.ukaachen.de for your application. There you have the option of securing your documents in the electronic application folder to prevent unauthorized access. Applications that reach us by e-mail to: bewerbung@ukaachen.de (this transmission path cannot be as effectively secured) will be transferred to the aforementioned portal and any accompanying documents will be disposed of in accordance with data protection regulations immediately after transfer. After the retention period has expired, the data in the portal will also be deleted. If you do not agree to a transfer to the Application portal your application cannot be considered.
Please enclose a CV, study transcripts, contact details, publication list, research statement, recommendation letter from two referees.
The application deadline for the advertised position GB-P-33305 is 13th June 2022.
University Hospital RWTH Aachen
Institut für Pathologie, Univ.-Prof., M.D., Ph.D., Peter Boor
Pauwelsstraße 30, D-52074 Aachen
If you have any further queries, please do not hesitate to contact Univ.-Prof., M.D., Ph.D., Peter Boor, e-mail: pboor@ukaachen.de
Visit our homepage www.labooratory.ukaachen.de.
Apply online now

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