Doctoral student in Mechnical Engineering Sciences - focusing on Multi-sensor process monitoring

Description of the workplace

The vacancy is situated in the Division of Production and Materials Engineering (IPROD) within the Department of Mechanical Engineering Sciences, LTH/LU. The division is involved in research, development, teaching, and industrial collaboration in the field of materials and production engineering. The projects undertaken are related to Industry 4.0, focusing on manufacturing processes and technology, digitalization of manufacturing processes and sustainable production. The subject area is interdisciplinary, often combining fundamental and applied research.

The division consists of approximately 25 colleagues, including six doctoral students and three postdoctoral researchers. Our premises are in the recently renovated M-building on LTH's campus in Lund. More information about the department can be found here: Division of Production and Materials Engineering

The project is carried out within Sentio – Integrated Sensors and Adaptive Technology for Sustainable Products and Manufacturing – which is a newly inaugurated competence centre coordinated by Lund University in close collaboration with companies from Swedish industry, RISE, Region Skåne and trade associations. The goal is to create a world leading highly interdisciplinary research centre that brings together the wide range of diverse competences from industry and academia that are needed to develop integrated sensor technology with the capacity to significantly improve sustainability, reduce the use of resources, and increase competitiveness across industrial sectors of Sweden.  In this first recruitment Sentio will hire 7 doctoral students within different areas of expertise who will all work together with the research within Sentio. Sentio is financed by Vinnova – Sweden’s innovation agency. More information about the competence center can be found here: Sentio
 

Work duties

As a doctoral student in the Smart Manufacturing group, you will explore new materials, processes, and approaches in modern manufacturing. The focus includes sensor-based process monitoring, optimization, and addressing industry research questions. Using advanced sensors and AI/ML tools, you will develop digital solutions for real-time monitoring and analysis, essential for understanding metal processing phenomena and advancing Smart manufacturing and engineering. You will plan, design, and conduct experiments with guidance from supervisors, particularly focusing on complex manufacturing processes like metal cutting operations.

The main duties of doctoral students are to devote themselves to their research studies which includes participating in research projects and third cycle courses. The work duties will also include teaching and other departmental duties (no more than 20%).

We also appreciate your participation in common tasks related to general institutional duties, seminars, knowledge transfer, and collaboration with industry, among others.

Admission requirements 

A person meets the general admission requirements for third-cycle courses and study programmes if the applicant: 

• has been awarded a second-cycle qualification, or
• has satisfied the requirements for courses comprising at least 240 credits of which at least 60 credits were awarded in the second cycle, or
• has acquired substantially equivalent knowledge in some other way in Sweden or abroad.

A person meets the specific admission requirements for third cycle studies in Mechanical Engineering Sciences if the applicant has: 

• at least 90 credits of relevance to the field, including at least 60 second-cycle credits, or
• a second-cycle degree in a relevant field

Finally, the student must be judged to have the potential to complete the programme.

Additional requirements:

• very good oral and written proficiency in English.
• solid theoretical knowledge in production and metal cutting operations.
• good theoretical knowledge in (non)linear dynamics.
• completion of at least one Programming course.

Assessment criteria

Selection for third-cycle studies is based on the student’s potential to profit from such studies. The assessment of potential is made primarily on the basis of academic results from the first and second cycle. Special attention is paid to the following: 

1. Knowledge and skills relevant to the thesis project and the subject of study.
2. An assessment of ability to work independently and to formulate and tackle research problems.
3. Written and oral communication skills.
4. Other experience relevant to the third-cycle studies, e.g. professional experience.

Other assessment criteria:

• experience in sensors and data acquisition, signal and image processing.
• ability (shown via, e.g. the master’s thesis) to develop, implement, and apply relevant scientific models to data and critically assessing the results.
• programming experience (preferably in Julia, Python, Matlab, or R).
• experience in Machine learning or related subjects such as: Time-series analysis, Spectral analysis, Statistical learning.

Consideration will also be given to good collaborative skills, drive and independence, and how the applicant, through experience and skills, is deemed to have the abilities necessary for successfully completing the third cycle programme.

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

Terms of employment 

Only those admitted to third cycle studies may be appointed to a doctoral studentship. Third cycle studies at LTH consist of full-time studies for 4 years. A doctoral studentship is a fixed-term employment of a maximum of 5 years (including 20% departmental duties). Doctoral studentships are regulated in the Higher Education Ordinance (1993:100), chapter 5, 1-7 §§.

How to apply

Applications shall be written in English and include a cover letter stating the reasons why you are interested in the position and in what way the research project corresponds to your interests and educational background. The application must also contain a CV, degree certificate or equivalent, and other documents you wish to be considered (grade transcripts, contact information for your references, letters of recommendation, etc.).

Welcome to apply!