PhD Candidate in Machine Learning and Data Mining for Lubricant Formulation
About the position
The Department of Mechanical and Industrial Engineering has a vacancy for a PhD candidate in machine learning and data mining for lubricant formulation in the Materials Group. We are looking for candidates with a background in one or ideally more of these areas: machine learning, computational science, statistics, data mining, statistical physics, theoretical chemistry, statistical modelling, applied mathematics.
The project deals with the use of data mining methods, especially machine learning, to extract useful information from chemical databases and experimental results. Lubricants are mixtures of a base lubricant and a large number of additives for different functions. Lubricantion is a complex problem with many different physical and chemical processes occurring on different length scales. As a result, modern lubricant formulation is still based on tweaking existing recipes. The new products are typically improved by trial and error. This long, expensive and often frustrating process can be boosted with the help of Artificial Intelligence (AI). Formulating lubricants requires gathering information of available chemicals and substances that have the physical and chemical characteristics required for providing a system with the desired friction and wear. Mining in the available data of chemicals that could potentially become the next generation of lubricants requires new tools, methods, and new approaches, radically different from those used until now.
The goal of this project is to develop new tools and methods for formulating new lubricants with potentially environmentally acceptable properties. There will be interaction with experimental researchers in the same project, who are collecting data, and with collaborators in Germany who work in the field of data mining and machine learning.
About the materials group
The materials group deals with applications of materials science: engineering materials and surfaces with desirable properties for specific applications. 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 young scientists.
You will report to Associate Professor Astrid S. de Wijn
Duties of the position
- Build data sets of lubricants and additives based on available experimental information.
- Use modern data mining techniques (such as artificial neural networks, but also statistical approaches) to analyse large data sets relating to lubricant and additive performance.
- Interpret the results in the context of the physical and chemical mechanisms involved.
- Compare the results to experimental data and suggest ways to improve performance, especially new lubricant additives.
Required selection criteria
The PhD-position's main objective is to qualify for work in research positions. The qualification requirement is that you have completed a master’s degree or second degree (equivalent to 120 credits) with a strong academic background in machine learning, computational science, statistics, data mining, statistical physics, statistical modelling, applied mathematics, or equivalent education with a grade of B or better in terms of NTNU’s grading scale. If you do not have letter grades from previous studies, you must have an equally good academic foundation. If you are unable to meet these criteria you may be considered only if you can document that you are particularly suitable for education leading to a PhD degree.
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, post doctor and research assistant.
Other required selection criteria
- Experience programming in a higher programming language (such as C or ideally python) and using Linux.
- Affinity for statistics or statistical modelling.
Preferred selection criteria
- Experience with atomic-scale physical or chemical modelling, or data mining.
- Good written and oral English language skills
- Experimental experience in chemistry will be seen as a plus
- Highly motivated, with enthusiasm for applied theoretical research.
- Interest in strong interacttion with experimental researchers.
- Be able to work both in a research team as well as carry out personal research projects.
- Good interpersonal skills.
- Strong analytical skills.
In the evaluation of which candidate is best qualified, emphasis will be placed on education, experience and personal suitability.
- 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
PhD candidates are remunerated in code 1017, and are normally remunerated at gross from NOK 479 600 per annum before tax, depending on qualifications and seniority. From the salary, 2% is deducted as a contribution to the Norwegian Public Service Pension Fund.
The period of employment is 3 years.
Appointment to a PhD position requires that you are admitted to the PhD programme in Engineering, https://www.ntnu.edu/studies/phiv within three months of employment, and that you participate in an organized PhD programme during the employment period.
The engagement is to be made in accordance with the regulations in force concerning State Employees and Civil Servants, and the acts relating to Control of the Export of Strategic Goods, Services and Technology. Candidates who by assessment of the application and attachment are seen to conflict with the criteria in the latter law will be prohibited from recruitment to NTNU. After the appointment you must assume that there may be changes in the area of work.
The position is subject to external funding.
It is a prerequisite you can be present at and accessible to the institution on a daily basis.
About the application
The application and supporting documentation to be used as the basis for the assessment must be in English.
Publications and other scientific work must follow the application. Please note that applications are only evaluated based on the information available on the application deadline. You should ensure that your application shows clearly how your skills and experience meet the criteria which are set out above.
Joint works will be considered. If it is difficult to identify your contribution to joint works, you must attach a brief description of your participation.
A good work environment is characterized by diversity. We encourage qualified candidates to apply, regardless of their gender, functional capacity or cultural background.
The city of Trondheim is a modern European city with a rich cultural scene. Trondheim is the innovation capital of Norway with a population of 200,000. The Norwegian welfare state, including healthcare, schools, kindergartens and overall equality, is probably the best of its kind in the world. Professional subsidized day-care for children is easily available. Furthermore, Trondheim offers great opportunities for education (including international schools) and possibilities to enjoy nature, culture and family life and has low crime rates and clean air quality.
NTNU is committed to following evaluation criteria for research quality according to The San Francisco Declaration on Research Assessment - DORA.
As an employee at NTNU, you must at all times adhere to the changes that the development in the subject entails and the organizational changes that are adopted.
Information Act (Offentleglova), your name, age, position and municipality may be made public even if you have requested not to have your name entered on the list of applicants.
If you have any questions about the position, please contact Associate Professor Astrid S. de Wijn, email: firstname.lastname@example.org, or Professor Nuria Espallargas, email: email@example.com.
Please submit your application electronically via www.jobbnorge.no with your CV, diplomas and certificates. Applications submitted elsewhere will not be considered. Diploma Supplement is required to attach for European Master Diplomas outside Norway. Chinese applicants are required to provide confirmation of Master Diploma from China Credentials Verification (CHSI).
If you are invited for interview you must include certified copies of transcripts and reference letters.
Please refer to the application number IV-117/20 when applying.
Application deadline: 27 May 2020
NTNU - knowledge for a better world
The Norwegian University of Science and Technology (NTNU) creates knowledge for a better world and solutions that can change everyday life.
Department of Mechanical and Industrial Engineering
We educate graduates who can create new products, operate and maintain products, and manage projects. The Department has a variety of bachelor’s and master’s degree programmes. We conduct wide-ranging research in fields such as technology, energy, product quality and development, and productivity. The Department of Mechanical and Industrial Engineering is one of eight departments in the Faculty of Engineering.
Deadline 27th May 2020
Employer NTNU - Norwegian University of Science and Technology
Place of service Dep. of Mechanical and Industrial Engineering