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Computational Postdoctoral Researcher

4 weeks ago


Bristol, Bristol, United Kingdom France - BioImaging Full time
Computational Postdoc: Predictive Modeling of Human Stem Cell Differentiation

We are seeking a highly motivated and talented computational postdoc to join our team at the University of Bristol. The successful candidate will have prior expertise in quantitative image analysis and machine learning, particularly in cell segmentation and tracking from multi-channel time-lapse fluorescence microscopy images.

The Carazo Salas group is establishing innovative experimental and computational tools and pipelines combined with human pluripotent stem cell technologies to elucidate the quantitative and mechanistic basis of efficiency, specificity, and tumourigenic potential in human pluripotent stem cell differentiation.

As a computational postdoc, you will be responsible for extracting information from images to understand and predict why each cell makes the fate decision it makes. You will work in an interdisciplinary environment with a team of researchers and engineers to develop novel approaches for predictive modeling of human stem cell differentiation.

Key responsibilities include:

  • Developing and implementing computational image analysis and machine learning algorithms for cell segmentation and tracking
  • Collaborating with experimental biologists to design and optimize experiments
  • Integrating data from multiple sources to develop predictive models of stem cell differentiation
  • Presenting research findings to the team and at international conferences

We are looking for a candidate with a PhD in Computational Image Processing, Computer Vision, Machine Learning, or a related subject, and extensive experience with computational image analysis and/or machine learning. Experience with timelapse microscopy imaging of cells or high-throughput/high-content microscopy is a plus.

Join our team and contribute to the development of innovative computational tools and pipelines for predictive modeling of human stem cell differentiation.