Senior research engineer: Senior Machine Learning Scientist with expertise in Biology of Infections

Department of Plant Physiology

Closing date: 2023-03-23.

As a national hub for molecular biosciences in Sweden, SciLifeLab develops and maintains unique research infrastructure, services and data resources for life science. The overall aim of SciLifeLab is to facilitate cutting-edge, multi-disciplinary life science research and promote its translation to the benefit of society. About 200 research groups, 1500 researchers and 40 national infrastructure units are associated with SciLifeLab, with two main centers located in Stockholm and Uppsala, but with national SciLifeLab units at all major Swedish universities.

The SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS) is a 12-year initiative that focuses on data-driven research, within fields essential for improving people’s lives, detecting and treating diseases, protecting biodiversity and creating sustainability. The program will train and recruit the next generation of data-driven life scientists and create strong and globally competitive computational and data science capabilities in Swedish life science. The program aims to strengthen national collaborations between universities, bridge the research communities of life and data sciences, and create partnerships with industry, healthcare and other national and international actors.

The DDLS program is now establishing a national Data Science Node in “Epidemiology and Biology of Infections” at Umeå university with a national responsibility to develop national data services and to provide advanced data analytics support including bioinformatics support. The Data Science Node staff will be well integrated with the local research community, but also connected to the SciLifeLab Data Centre and the SciLifeLab National Infrastructures, in particular the Bioinformatics Infrastructure Platform (National Bioinformatics Infrastructure Sweden, NBIS), a unique national infrastructure with over 100 experts employees, providing advanced bioinformatics support, infrastructure and training to the Swedish life science research community and participating in international collaborations. 

We are now looking for outstanding candidates with expertise in AI, machine learning and statistical methods applied in a biological context related to infection biology with the aim to increase our understanding of the emergence, prevalence and spread of infectious disease. As a senior research engineer within applied machine learning, you will apply, adapt and develop machine learning approaches to provide data analysis support to data-driven Swedish research projects of scientific excellence as well as being a driver of advanced data analytics postgraduate training on a national level.

Your future workplace

The Department of Plant Physiology hosts the largest bioinformatic section of Umeå university with over 20 bioinformaticians and the Swedish Metabolomic Facility. You will work in a strong group of bioinformaticians that both helping other scientist with analysis and are developing the field themselves. The bioinformatic group work with projects from all fields of life science. 

The department is part of the Umeå Plant Science Centre with total over 200 scientists in more than 35 research groups and with a strong, multi-disciplinary, collaborative and expanding research. We are also a strong partner in The Chemical-Biological Centre (KBC), a life science hub that hosts several national instrument and technology platforms. For more information about working at Umeå University: www.umu.se/en/work-with-us/. 

Main responsibilities

The main responsibilities are to:

• Carry out advanced data analyses within nationally prioritized data-driven life science projects, using state-of-the-art machine learning tools applied to large-scale molecular (omics), imaging, clinical and/or epidemiological data.
• Develop and implement necessary tools and workflows for such analyses.
• Educate other life scientists across Sweden in advanced data analytics through collaboration within supported projects, give support at advanced national courses and consultations.
• Engage in the continuous development and improvement of the DDLS program, the Data Science Node, and the SciLifeLab Bioinformatics platform.

Qualification requirements

We are looking for a highly motivated candidate with strong skills in applying AI/machine learning and statistical modeling methods focused on infection biology. The successful candidate has 

(i) Ph.D. in Biotechnology, Engineering, Physics or equivalent 

(ii) Extensive (3+ years) experience of applying advanced AI or machine learning methods in a biological context. 

(iii) Strong programming knowledge in Python, including knowledge of common data science tools such as Numpy, Pandas and Matplotlib, and version control using Git.

(iv) Experience using modern deep learning frameworks (such as PyTorch or Tensorflow)

(v) Experience in working with real world large scale life science data is required

(vi) Very good oral and written communication skills in English

(vii) Strong skills in cooperation and communication

Additional qualifications

Relevant postdoctoral studies or industry experience are a strong merit but not a requirement. Experience of research or development connected to epidemiology and biology of infections or other public health questions is a strong merit. Experience in either machine learning management systems such as Azure ML, machine learning workflow-engines such as MLFlow/Airflow/Metaflow, or data storage, databases, and structure for large data volumes is also a strong merit.  “Reproducible research” and “FAIR data” are central concepts to us, and expertise in the development of reproducible code by using code sharing platforms, workflow languages and container solutions is a merit.

Terms of employment

The employment is full-time and permanent. Probationary employment may be applied. Starting date 2023-05-01 or according to agreement.

Application

Your application should contain 

• A personal letter, max 2 pages, including a motivation for why you want to join this effort
• CV with publication list
• Doctoral degree certificate

You apply via our recruitment system Varbi. Last application date is 2023-03-23.

Contact

Björn Nystedt, NBIS Support Manager, tel +46 18 471 44 13, bjorn.nystedt@scilifelab.se
Johan Trygg, UmU DDLS Data Science Node, tel +46 730 647 137, johan.trygg@umu.se
Johannes Hanson, Inst. fysiologisk botanik, tel +46 722 243 283, Johannes.hanson@umu.se