Lund University, Faculty of Engineering, LTH, Dept of Mechanical Engineering

Lund University was founded in 1666 and is repeatedly ranked among the world’s top universities. The University has around 47 000 students and more than 8 800 staff based in Lund, Helsingborg and Malmö. We are united in our efforts to understand, explain and improve our world and the human condition.

Lund University welcomes applicants with diverse backgrounds and experiences. We regard gender equality and diversity as a strength and an asset.

Description of the workplace

The position is situated in the Division of Production and Materials Engineering (IProd) at the Department of Mechanical Engineering Sciences, LTH/LU. The division conducts research, development, teaching and industrial collaboration in the field of materials and production engineering with projects such as on Industry 4.0, machining, digitalization of manufacturing processes and sustainable production. The subject area is interdisciplinary and is often on the crossroad of the fundamental and applied research. In the context of Industry 4.0, sensor-based process monitoring, and decision making are used to generate fundamental understanding of the production processes and their optimization and to study research questions set by industry. We are interested in new materials, processes, and approaches to achieve understanding of fundamental dynamic processes in modern manufacturing. Our research group is of 25 senior and junior research personnel.

Subject description

The scope of the current project includes the development of Intelligent Solutions to monitor and assist metal-cutting processes for selected machining processes. The goal is to optimize machinability of materials, used in automotive and aerospace industries when MQL-assisted machining. Expected Intelligent Solutions should be based on explainable and interpretable mathematical approaches, and Data Mining for observed physical and dynamic phenomena of selected machining operations.

The research focus is on study, monitor, and analysis of the selected machining processes, which can be done through modelling by using physical and mathematical (including Artificial Intelligence (AI) / Machine Learning (ML)) approaches.

Work duties

The main duties involved in a post-doctoral position is to conduct research. Teaching may also be included, but up to no more than 20% of working hours. The position includes the opportunity for three weeks of training in higher education teaching and learning. The purpose of the position is to develop the independence as a researcher and to create the opportunity of further development.

The Division of IProd at the Department of Mechanical Engineering Sciences needs to recruit a postdoctoral researcher in the mentioned above subject area.

The aim of the project is improvement of machinability of selected materials by developing an intelligent solution for adaptive control of MQL-assisted machining with use of biobased lubricants and additives. The focus areas of the project are “End-to-end AI in development, production and services” and “Model- and simulation-driven development and optimization”. The main effort will be on research of physics of MQL-assisted machining, tool degradation when using eco-friendly lubricants. Equally important is the focus on development of models (Digital Twins) of metal cutting-related phenomena resulting in optimization of machinability of selected materials (GCI, Ti-, Al- and Ni-alloys). Particular focus will be on the development of adaptive system for MQL-assisted machining based on physics- and data-driven smart solutions with use of Sensor Fusion, Computer Vision, and light robotics for optimization of process performance.

The project is related to the engineering area of tooling and automotive industries (e.g. Seco Tools, Volvo Group Trucks Operations, Hydro). Experimental work will be performed at the Division of Production and Materials Engineering in Lund University and partially at industrial site.

As a postdoctoral fellow, you will be responsible for the development of project ideas, planning, designing, and executing experiments independently, and in collaboration with academic supervisors and industrial partners.

We would like you to participate in common tasks related to general institutional tasks, seminars, knowledge transfer and cooperation with industry, etc.

Qualification requirements

Appointment to a post-doctoral position requires that the applicant has a PhD, or an international degree deemed equivalent to a PhD, within the subject of the position. The certificate proving the qualification requirement is met, must be received before the employment decision is made. Priority will be given to candidates who have graduated no more than three years ago before the last day for application. Under special circumstances, the doctoral degree can have been completed earlier.

Additional requirements:

  • You have very good oral and written proficiency in English.
  • You have a doctoral degree within mechanical engineering, data science or automatic control with a mechanical engineering background.
  • You have minimum one year of hands-on experience of studying manufacturing processes for the purpose of process monitoring and diagnostics.
  • You have good problem-solving and linguistic analytical abilities.
  • You are expected to work independently, but also to interact with the academic and industrial collaborators, and researchers from other subjects.
  • You are structured and goal-oriented.

Assessment criteria

This is a career development position primarily focused on research. The position is intended as an initial step in a career, and the assessment of the applicants will primarily be based on their research qualifications and potential as researchers. Particular emphasis will be placed on research skills within the subject.

For appointments to a post-doctoral position, the following shall form the assessment criteria:

  • A good ability to develop and conduct high quality research.
  • Teaching skills.

Other qualifications:

Experience in any of the following areas will be considered an asset:

  • Documented theoretical or practical experience in the research area of manufacturing processes, especially cutting processes in aerospace and automotive fields.
  • Demonstrated experience of using high-level programming languages.
  • Experimental work related to the research in mechanical engineering including manufacturing processes.
  • Hands-on experience in development and implementation of Artificial Intelligence (AI) -based smart solutions.
  • Demonstrated knowledge of Dynamics (mechanical vibrations), Signal and Image Processing, Dynamic System Identification, Robotics, and Artificial Intelligence (AI) including Deep Learning and Machine Learning.
  • Demonstrated knowledge of Industry 4.0 concepts.

Consideration will also be given to how the applicant’s experience and skills complement and strengthen ongoing research within the department, and how they stand to contribute to its future development.

We offer

Lund University is a public authority which means that employees get particular benefits, generous annual leave and an advantageous occupational pension scheme.
Read more on the University website about being a Lund University employee Work at Lund University.

Further information

This is a full-time, fixed-term employment of 2 years. The period of employment is determined in accordance with the agreement “Avtal om tidsbegränsad anställning som postdoktor” (“Agreement on fixed-term employment as a post-doctoral fellow”).

How to apply

Applications shall be written in English. Please draw up the application in accordance with LTH’s Academic qualifications portfolio – see link below. Upload the application as PDF-files in the recruitment system (including your PhD certificate). Read more: To apply for academic positions at LTH.

Welcome with your application!

Type of employment Temporary position
Contract type Full time
First day of employment Enligt överenskommelse
Number of positions 1
Full-time equivalent 100 %
City Lund
County Skåne län
Country Sweden
Reference number PA2024/250
  • Oleksandr Gutnichenko,
Union representative
  • OFR/ST:Fackförbundet ST:s kansli, 046-2229362
  • SACO:Saco-s-rådet vid Lunds universitet,
  • SEKO: Seko Civil, 046-2229366
Published 22.Jan.2024
Last application date 14.Mar.2024 11:59 PM CET

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