Database manager/Data Engineer with AI / Machine Learning Expertise

Örebro University seeks to appoint a Database manager/Data Engineer with established expertise in Machine Learning. This position is jointly offered by three research groups at Örebro University: AASS, MTM/EnForce, and Functional Bioinformatics. AASS is one of the nationally leading research groups in robotics, AI and applied Machine Learning, frequently involved in computer vision analysis as well as AI applications producing big data from robot-environment and robot-human interactions. The MTM/EnForce Centre at Örebro University focuses on environmental toxicant discovery and hazard assessment using advanced analytical methods, bioassay technologies, among these an image-analysis based ”cell painting” assay system, and effect-directed analysis. The Functional Bioinformatics group conducts research in applying and further developing machine learning approaches for pattern discovery in biomedicine, e.g. biosignatures for diagnosis, prediction, and prognosis, as well as for systems for biological applications, e.g. network biology and network medicine, where the newly available infrastructure for AI analyses should be made available for clinical application pilot projects.

Duties and responsibilities
The candidate will work closely together with AASS, MTM/EnForce and Functional Bioinformatics and bring in their Machine Learning (ML) expertise in the respective projects. The selected candidate will represent and apply this expertise and take responsibility for the technical infrastructure as well as specific data management. The successful candidate will work with implementation of AI on the existing high-performance hardware (GPU cluster) at Örebro University as well as at SNIC, the Swedish national infrastructure for computing (e.g. UPPMAX and BIANCA at Uppsala University). The candidate will contribute to development of data processing pipelines and AI-based automation of cellular image analysis. Cluster management, user management and data management regarding the specific needs of AI-related analyses and infrastructure are a specific focus of this position.

Eligibility
We are looking for candidates who are excited about applying Machine Learning techniques in robotics and life science and are keen to have a strong, positive impact on society. The successful candidate should have a strong background in Machine Learning/AI, demonstrated by their previous work.

Assessment criteria
The assessment of the candidates is based on previous work and the suitability to the position outlined above, as well as demonstrated programming and deployment skills. It is a plus if the candidate can document previous work with Machine Learning. Experience with high-performance computing (both CPU and GPU clusters) is of special interest. It is not necessary to be familiar with the Swedish language, but excellent communication skills in English, both written and spoken, are a requirement. The position especially requires good interpersonal skills, in particular the ability and interest to cooperate in a highly interdisciplinary context, as the focus is to contribute with their AI engineering competence collaborating with a number of researchers at the various research groups.

Equality
Our ambition is to create a workplace that is characterised by gender equality and diversity.

Information
The position is a full-time, permanent position, based in Örebro. The salary depends on the successful candidate’s qualifications and experience. Positions announced at Örebro University are, where appropriate, subject to a trial period. This position offers a competitive salary that depends on the successful candidate's qualifications and experience.

For more information about this position, please contact Prof. Achim J. Lilienthal (especially questions about AASS, robotics, computer vision and AI) by email at achim.lilienthal@oru.se, Prof. Dirk Repsilber (especially questions about Functional Bioinformatics, Big Data and pattern discovery in biomedicine/medicine using Machine Learning) at dirk.repsilber@oru.se or Prof. Magnus Engwall (environmental toxicology, image analysis, cell painting, and effect-directed analysis) at magnus.engwall@oru.se.

Application
The application is made online. Click the button “Apply” to begin the application procedure.

For the application to be complete, the following electronic documents must be included:


• Cover letter
• CV
• Copies of relevant course/degree certificates and references
• List of at least two references (with name, affiliation, phone number)
• Any other relevant documentation

Only documents written in English, Swedish, Norwegian and Danish can be reviewed.

The application deadline is 26 April 2020. We look forward to receiving your application!

We decline any contact with advertisers or recruitment agencies in the recruitment process.

As directed by the National Archives of Sweden (Riksarkivet), Örebro University is required to deposit one file copy of the application documents, excluding publications, for a period of two years after the appointment decision has gained legal force.