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Stillingstittel:
Data mining and machine learning for tribology (SO IV-24/19)

Stillingsbeskrivelse:

This is NTNU

At NTNU, creating knowledge for a better world is the vision that unites our 7 000 employees and 40 000 students.

We are looking for dedicated employees to join us.

   

Video: https://www.youtube.com/watch?v=cIgKd1SwGLI

About the position

We have a vacancy for a postdoctoral fellow in the Materials group at the Department of Mechanical and Industrial Engineering, under the supervision of Associate Professor Astrid S. de Wijn.

The project deals with the use of data mining methods, especially machine learning, to extract useful information from large data sets of measurements of surface properties, especially relating to friction, lubrication, and wear. Friction is a complex problem with many different physical and chemical processes occurring on different length scales. Today, there is not sufficient quantitative understanding of all of these processes to be able to predict friction for applications. This is why technological development is often done by trial and error, and step by step improvements, which is extremely time-consuming. A lot of testing is done on different materials and combinations, and there is a lot of experimental data, but little understanding. In order to guide the development of materials it is essential to make better use the information hidden in the wealth of experimental data. Because friction is such a complex process, much of this information is hidden, i.e. not immediately obvious by direct human inspection. This is exactly the type of problem that machine learning algorithms are designed for.

The goal of the project will be to apply advanced data mining and machine learning techniques to  large data sets on performance of surface treatments that have been collected in the field. There will be interaction with the industrial partners who are collecting the data, and with collaborators in Germany who work in the field of data mining and machine learning.

The person filling this position will be working in the modelling and tribology subgroup of the materials group.  The Materials group deals with materials applications: engineering materials and surfaces - manufacturing, properties and components. The group consists of an interdisciplinary mixture of engineers, physicists, and chemists. We have many industrial and international academic collaborations and aim to provide a stimulating environment for research and learning.

The position reports to the head of department and is supervised by Associate Professor Astrid S. de Wijn.

Job abstractJV_description

• Use modern data mining techniques (such as artificial neural networks, but also statistical approaches) to analyse large data sets relating to material performance and degradation.
• Interpret the results in the context of the physical and chemical mechanisms involved.
• Use this information to suggest ways to improve performance, for examply by constructing automated decision-making tools for surface treatments or monitoring.

Qualification requirements

Postdoctoral fellow:
A postdoctoral research fellowships is a qualification position in which the main objective is qualification for work in academic positions. Completion of a Norwegian doctoral degree in [subject area] or corresponding foreign doctoral degree recognized as equivalent to a Norwegian doctoral degree is required.

The appointment is to be made in accordance with the regulations in force concerning State Employees and Civil Servants and national guidelines for appointment as PhD, postdoctor and research assistant

• Affinity for statistics or statistical modelling.
• Experience with modelling of materials, statistical physics, or data mining.
• A history of publications and/or conference attendance in relevant fields.
• Experience programming in a higher programming language (such as C or ideally python) and using Linux.
• Good written and oral English language skills.

Personal characteristics

• Highly motivated.
• Able to work both in a research team as well as carry out personal research projects.
• Enthusiasm for applied research.

In the evaluation of which candidate is best qualified, emphasis will be placed on education, experience and personal suitability, as well as motivation, in terms of the qualification requirements specified in the advertisement

We offer

• exciting and stimulating tasks in a strong international academic environment
• an open and inclusive work environment with dedicated colleagues
• favourable terms in the Norwegian Public Service Pension Fund
• employee benefits

Salary and conditions

Postdoc:
Postdoctoral candidates are remunerated in code 1352, and are normally remunerated at gross from NOK 515 200 before tax per year. From the salary, 2 % is deducted as a contribution to the Norwegian Public Service Pension Fund.

The period of employment is 2 years.

Appointment takes place on the terms that apply to State employees at any time, and after the appointment you must assume that there may be changes in the area of work.

General information

Working at NTNU

A good work environment is characterized by diversity. We encourage qualified candidates to apply, regardless of their gender, functional capacity or cultural background. Under the Freedom of Information Act (offentleglova), information about the applicant may be made public even if the applicant has requested not to have their name entered on the list of applicants.

Questions about the position can be directed to Dr. Astrid S. de Wijn, phone number +4773597098,  e-mail astrid.dewijn (at) ntnu.no

About the application:
Publications and other academic works that the applicant would like to be considered in the evaluation must accompany the application. Joint works will be considered. If it is difficult to identify the individual applicant's contribution to joint works, the applicant must include a brief abstractJV_description of his or her contribution.

Please submit your application electronically via jobbnorge.no with your CV, diplomas and certificates. Applicants invited for interview must include certified copies of transcripts and reference letters. Please refer to the application number 24/19 when applying.

Application deadline: 09.01.2019

Se annonsen og søk på stillingen www.jobbnorge.no

numberOfPosts: 1

jobCategoriesCodes_0: http://data.europa.eu/esco/isco/C2511

abstractJV_contact_0: See jobabstractJV_description

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