HASTE: Hierarchical Analysis of Spatial and Temporal Data
From intelligent data acquisition via smart data-management to confident predictions
We are happy to present our newest member of HASTE: Dan Rosén! Dan is joining the group of Ola Spjuth to work as a Data Engineer. In his projects he will work with data pipelines and interact closely with microscopes to help reaching the goals of HASTE to act on collected image streams and make intelligent decisions and control microscopes to prioritize collecting the most interesting data.
We are looking for a skilled Data Engineer to join the HASTE team!
In collaboration with other researchers, develop, implement and test systems for AI-controlled automated microscopes. The task includes interacting directly with the microscope and establishing pipelines where models trained on previously taken images decide and control where the microscope should take images in the next step to reach a specific goal. We are looking for a candidate with a genuine interest in technology and automation, and who enjoys solving problems including both practical interaction with hardware (robots, microscopes) and different types of software. Since our microscopes generate large amounts of images, the position will also include large-scale data management and -analysis. You will work with researchers in AI modeling and biological laboratory sciences, and contribute to implementing methods and evaluating them for different types of biological problems.
This is a 2-year position that is part of the HASTE project, funded by the Swedish Foundation for Strategic Research (SSF) aiming at developing new, intelligent ways of processing and managing very large amounts of microscopy images in order to be able to leverage the imminent explosion of image data from modern experimental setups in the biosciences. Industry collaborators are Vironova AB and AstraZeneca AB.
A master’s degree in engineering or a university degree in a relevant field is a requirement. Good programming skills in Python and preferably more programming languages is a requirement. Experience in AI modeling, Linux systems as well as developing REST services and APIs is a requirement. Experience of AI modeling on image data, practical handling of automated microscopes and working with software containers (e.g. Docker/Singularity) is meriting.
Apply via link at the bottom of the University application: https://uu.se/en/about-uu/join-us/details/?positionId=361223
Deadline: Nov 25th, 2020
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: https://www.uu.se/en/about-uu/join-us/details/?positionId=327845 (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
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.
Discovering new drugs is becoming more costly. Lars Carlsson gave a presentation Machine Learning For Smarter Drug Discovery at RISE SICS Data Science & AI Day, Nov 28, 2017, where he gave some examples of how AstraZeneca is trying to improve the drug discovery phases through the use of machine learning.
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.
We are recruiting two PhD students in Computerized Image Processing and Bioinformatics. For more information, see the recruitment page.
We are recruiting up to three postdocs or researchers in Computerized Image Analysis, Scientific Computing and Bioinformatics. For more information, see the recruitment page.
