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PhD student (f/m/d) – Deep Learning/Computer Vision/Computational Biology for Bioimage Analysis

Location:
Research group:
Working hours:

Vienna

Sabine Taschner-Mandl Group

full-time

Are you looking to put your computational skills to the test? 
Are you fascinated by cancer biology and using multi-omics data to devise new treatment avenues?
Then this project is for you!

 

For a recently funded Excellence Program (www.fwf.ac.at/en/research-radar/10.55776/EFP45) we are looking for a PhD student (f/m/d) for computational analysis of multi-modal tissue imaging with a focus on deep learning and computer vision. In this role, you will work in a leading center for pediatric oncology. The Taschner-Mandl Lab tackles unresolved questions of pathogenesis of cancer in children using experimental and computational approaches (Fetahu IS, Nat Comms, 2023, Kromp F, IEEE Trans Med Imaging, 2021). You will have the unique opportunity to focus on developing advanced computational tools and methods for analyzing multi-modal tissue imaging and single-cell omics data, ultimately contributing to the creation of innovative cellular therapies to combat osteosarcoma, a severe pediatric cancer.

 
 

Your responsibilities

You will:

  • Analyze multi-modal high-plex images and spatial omics to identify clinically relevant biological signals.
  • Develop and rigorously evaluate novel machine learning and deep learning methods, particularly in computer vision, for advanced bioimage analysis.
  • Contribute to a prestigious research program with a clear and impactful mission.
  • Collaborate within a dynamic, multi-disciplinary research team and receive joint supervision from computational and biological experts.
  • Author manuscripts, present research findings at scientific conferences, and participate in advanced courses.
  • Apply for PhD fellowships and acquire skills in obtaining research funding.
  • Supervise and support junior team members, promoting a collaborative research environment.
 
 

Your profile

What you bring for this position:

  • MSc degree (obtained or in final stages) in bioinformatics, systems biology, computer science, or related fields
  • Background in molecular and cancer biology
  • Experience in NGS, bioimage or spatial tissue analysis
  • Solid understanding of statistics and mathematical principles
  • Proven experience in machine learning and deep learning, especially computer vision
  • Skills in maintaining and creating code repositories (e.g., GitHub)
  • Proficiency in deep learning libraries such as PyTorch or TensorFlow, and programming languages such as Python and preferably R
  • Well-organized and self-motivated team player with proactive “getting things done’’ mentality
 
 

Our offer

Does this sound interesting? This is our offer to you:

 
 

Who we are

The St. Anna Children’s Cancer Research Institute (St. Anna CCRI), located in the center of Vienna, the most livable city in the world and one of the most important sites for biomedical research in Europe. St. Anna CCRI is a multidisciplinary and internationally networked center of excellence whose goal is to contribute to a sustainable improvement in the cure rates of childhood and adolescent cancers through innovative research and development. Due to the close cooperation between clinic and research, St. Anna CCRI offers the ideal environment for cutting-edge research at a high international level and its implementation in clinical practice. and its translation into clinical practice.

St. Anna CCRI is an equal opportunity employer. We value diversity and are committed to providing a work environment of mutual respect to everyone without regard to race, colour, religion, national origin, age, gender identity or expression, disability, or any other characteristic protected by applicable laws, regulations and ordinances.

Find more information here: https://ccri.at/

Your application

We are looking forward to your application! Applications should at least contain your Curriculum Vitae, a cover letter, the contact details of three references, and a link to your GitHub profile (if available).

The application deadline is the 30.09.2024 . Applications will be reviewed on a rolling basis until the position is filled.