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Postdoctoral position (2 years) in multivariate analysis and deep learning [Umeå, Sweden]


Help develop new e-science methods that fundamentally integrates Deep Learning and Multivariate analysis. The postdoc position is full-time for a period of two years



Umea
At: Umeå University
Location: Umeå, Sweden
Web: www.umu.se

Department of Chemistry, Umeå University, Umeå, Sweden, is looking for a postdoc to a project where we will develop new e-science methods that fundamentally integrates Deep Learning and Multivariate analysis. The main task for the postdoc will be to conduct R&D in multivariate analysis and deep learning. The employment is full-time for a period of two years with starting date as soon as possible or as agreed between the two parties.

Project description and working tasks

In recent years, new tools, concepts and technologies, have brought new hope for fundamental understanding of chemistry, biology and medicine to drive the future development of systems medicine and systems biology. The main drivers have been new pioneering technologies (e.g. robotics, analytics, AI) in instruments that will fundamentally transform how research is conducted and the results thereof. Deep learning and multivariate analysis have both proven to be key data driven modelling technologies for delivering on this promise. The goal of this project is the integration of these new advanced data analytics solutions that builds on the complementary values of deep learning and multivariate analysis to model complex systems.

In this project we will develop new e-science methods that fundamentally integrates deep learning and multivariate analysis. We will apply and validate these methods in several ongoing projects, among others “Wine as a system” project - in collaboration with Stellenbosch, South Africa and Umeå Plant Science Centre (UPSC), from where we will take benefit of large-scale systems biology data, in a truly ambitious, yet realistic attempt to study wine from a systems biology perspective.

More specifically, this project will be focused on hybrid modeling, meaning integration of different modeling techniques, for example how multivariate analysis technology can be used to train and fine-tune deep learning models and vice-versa, how deep learning can be used as pretreatment tool for multivariate analysis.

In the working tasks are included:

  • Conducting R&D in multivariate analyses and deep learning
  • Developing methods for deep learning based analysis of unstructured data
  • Developing state-of-the-art algorithms in deep learning including methods for improving interpretation and robustness of deep learning models
  • Developing new workflows for efficient training of deep learning models when labels are scarce.

Qualifications

The required qualification is a doctoral degree or a foreign degree that is deemed equivalent in computer science, computer engineering, mathematics, physics or equivalent. To be eligible the degree must have been completed a maximum of three years before the end of the application period unless certain circumstances exist.

A solid understanding of linear algebra, algorithms, machine learning, optimization, numerical methods is required as well as experience with data science tools including scripting, preferably in Python. Good skills in English both spoken and written are required. A structured and solution-oriented approach and good communication skills and ability to work in a team are also requirements. Experience in Design-of-Experiments and data analytics is desirable.

Application

The application must contain the following documents:

 

  • A cover letter that describes qualifications, research interests, and motivation for application (maximum 2 pages)
  • A curriculum vitae, including a publication list
  • A copy of PhD thesis and relevant publications
  • A copy of doctoral degree certificate or equivalent and other relevant degree certificates and grades,
  • Name and contact information of at least two reference persons
  • Other relevant documents

Application should be written in English or Swedish. Applications must be submitted via our e-recruitment system Varbi no later than October 2, 2019.

Apply here.

For more information please contact Professor Johan Trygg, email:
johan.trygg@umu.se

Information about the department

Department of Chemistry is the largest department in the Faculty of Science and Technology, with approximately 200 employees, including about 40 doctoral students, and with a strong and expanding research. Three major areas of research; Biological Chemistry, Environmental and Biogeochemistry and Technical Chemistry, represents the research and chemistry education of our department. We are also a strong partner in KBC, The Chemical-Biological Centre. For more information about working at Umeå University:

www.umu.se/en/work-with-us/

 


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