Postdoc: Network inference from single cell perturbational data

The Project: Lead the development of machine learning methods to map signaling pathways from combinatorial CRISPR screens with single-cell RNA-seq read-outs in breast and pancreatic cancers. Closely interact with experimentalists in the lab in an iterative computational- experimental cycle.

Your Profile: PhD in a quantitative discipline, eg bioinformatics, physics, statistics, etc; Expert coding in R or Python; Experience with version control, container and package management systems, and workflow managers; Commitment to transparency, reproducibility and Open Science; Experience with machine learning and deep learning are a plus

The Lab: The Markowetz lab is a mixed computational/experimental lab. We are a team and support each other. You have the independence to develop your own ideas. The lab has been a jumping board for many successful careers in academia, industry, and spin-outs.

How to apply: Please follow the instructions on https://www.jobs.cam.ac.uk/job/32995 (Reference: SW29583)

 

Postdoc: Data integration and deep learning in pathology

The Project: Lead the development of machine learning methods for clinically important diagnostics questions in oesophageal, breast and ovarian cancer. Focus on deep learning for pathology images plus data integration of paired genomic profiles. Established close collaborations with oncologists and pathologists.

Your Profile: PhD in a quantitative discipline, eg bioinformatics, physics, statistics, etc; Expert coding in R or Python; Experience with version control, container and package management systems, and workflow managers; Commitment to transparency, reproducibility and Open Science; Experience with machine learning and deep learning are a plus

The Lab: The Markowetz lab is a mixed computational/experimental lab. We are a team and support each other. You have the independence to develop your own ideas. The lab has been a jumping board for many successful careers in academia, industry, and spin-outs.

How to apply: Please follow the instructions on https://www.jobs.cam.ac.uk/job/32997/ (Reference: SW29585)

 

Please read the Guide to Applicants before applying.

Unless otherwise noted apply at jobs.cam.ac.uk.

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