Postdoc position: AI methods for large-scale microscopy imaging

We are currently looking for an ambitious, highly motivated Postdoc with a good background in AI and imaging to join the HASTE project.

This is a 2-year postdoc position. Assignments include development and application of methods for large-scale analysis of microscopy images using AI / Machine Learning within the framework of the HASTE project. The project focuses on AI / machine learning with quantifiable confidence or probability, based on methods such as Active Learning, Conformal Prediction, Probabilistic (Venn) Prediction, and Deep Learning. Applicants are expected to collaborate with other project members and participate in regular research visits with industry partners AstraZeneca and Vironova.


PhD degree or a foreign degree equivalent to a PhD degree in a relevant field. The PhD degree must have been obtained no more than three years prior to the application deadline. The three year period can be extended due to circumstances such as sick leave, parental leave, duties in labour unions, etc. Documented experience with AI / ML methods and / or computerized image analysis. Experience in programming in eg Python is a requirement. Applicants should have excellent communication skills and be keen to actively interact with other team members including biologists, systems developers and researchers in AI / ML. Furthermore, applicants should be curious and creative, take initiatives and build relationships. Applicants should have good organizational ability, be able to structure work with multiple projects and solve anticipated and unexpected problems. The applicant must be able to express themselves very well in written and oral English

Apply via link at the bottom of the University application: (Please note: You MUST apply to the position via the form at Uppsala University, do not send any application documents to Ola Spjuth by email.)

If you have any questions regarding the project, please contact group leader Ola Spjuth.

Deadline to apply: May 7th, 2020

HASTE group at the conference: Phenotypic Screening, High-Content Analysis and AI: Overcoming the Challenges

Many in the HASTE team visited the conference: Phenotypic Screening, High-Content Analysis and AI: Overcoming the Challenges that was held March 2-3rd at AstraZeneca, Gothenburg, Sweden.

Ola Spjuth shared the session AI and Machine Learning where Carolina Wählby (PI of HASTE) and Phil Harrison (PhD student in HASTE) gave presentations.

Prof. Carolina Wählby (PI of HASTE) and Phil Harrison (PhD student in HASTE) were both part of the Expert Panel discussing “AI and Machine learning in Phenotypic Screening”.

Phil Harrison joins the HASTE team to work on predictive modeling with confidence

We welcome Phil Harrison as new PhD Student in the Spjuth lab. Phil obtained his first PhD in marine biology in 2006 studying the population dynamics of grey seals. Between 2006-2016 he undertook several research projects modelling wildlife populations and analysing trends in biodiversity. In the HASTE project, Phil  will develop machine learning methods for online, large-scale analysis of microscopy image data based on statistical earning including e.g. conformal prediction and probabilistic prediction.