PhD Student in Wood Science and Engineering – development of an artificial intelligence framework for sawmill process optimization

Lulea University
September 30, 2023
Offerd Salary:Negotiation
Working address:N/A
Contract Type:Other
Working Time:Negotigation
Working type:N/A
Ref info:N/A

Luleå University of Technology is in strong growth with world-leading competence in several research areas. We shape the future through innovative education and ground-breaking research results, and based on the Arctic region, we create global social benefit. Our scientific and artistic research and education are conducted in close collaboration with international, national and regional companies, public actors and leading universities. Luleå University of Technology has a total turnover of SEK 1.9 billion per year. We currently have 1,840 employees and 17,670 students.

In the coming years, multi-billion investments will be made in large projects in Northern Sweden to create a fossil-free society both nationally and globally. Luleå University of Technology is involved in several of these cutting-edge research projects and in the societal transformation that they entail. We offer a broad range of courses and study programmes to match the skills in demand. We hope that you will help us to build the sustainable companies and societies of the future.

We are looking for a motivated doctoral student for the research subject Wood Science and Engineering at Luleå University of Technology (LTU) who can carry out qualified research in our research group, both independently and in collaboration with colleagues. You will work within the strategic research program CT WOOD Centre of Excellence, which focuses research activities on X-ray computed tomography (CT) on wood. Most of the research within CT WOOD is conducted at the department of Wood Science and Engineering in Skellefteå. CT WOOD receives funding from The Swedish Forest Industry Federation (Swedish Wood), Kempe Foundations, Skellefteå Municipality and LTU, and several companies from the wood industry (Homepage). Additional funding for this position is provided by the Swedish Energy Agency (Energimyndigheten).

This unique doctoral position will lead to future in-demand expert competence and give you the opportunity to work in a creative research environment at LTU with researchers from highly diverse backgrounds, as well as in the organizations and companies we collaborate with.

Subject description Wood Science and Engineering includes an interdisciplinary approach on the wood material and industrial processes covering the value chain from forest to wood products. Research areas are anatomy, physics, chemistry, and mechanics related to wood, as well as wood processing and products engineering, manufacturing technology, process optimization and visualization for wood- based products.

Project description The main objective for this research position is to implement machine learning methods as part of a greater artificial intelligence (AI) framework for the sawmill industry. A key task is to increase the level of integration of the data flow in the sawmill process using X-ray CT (computed tomography) technology. The AI framework should ultimately lead to a digital twin of a cutting-edge sawmill process for prediction and optimization of the product output. The data you are intended to work with are primarily derived from CT scans of timber (logs and boards), which will mainly be collected at our CT lab in Skellefteå. ML should be used for three main tasks of the envisioned AI framework: 1) development of algorithms that reduce noise and enhance the visibility of quality-essential features in CT-scanned logs, 2) development of methods that automate the creation of 3D virtual logs with parametrized segmentation of the quality-essential features, 3) development of combined physics-informed and learning-based models (e.g. PINNs) to predict the mechanical properties of construction timber.

The project is motivated by the increased demand for renewable and sustainable building materials, which makes it necessary to improve the use efficiency of our forest resources. The final AI framework could finally enable the prediction of the timber quality (stiffness, strength, appearance) already before sawing, resulting in a much more efficient process.

During your research, you will be collaborating with experts in image-based AI from KTH Royal Institute of Technology (Department of Mathematics), researchers experienced in CT-scanning of wood and large industry partners from the CT WOOD initiative. Great opportunities exist for international cooperation with the most advanced research groups concerning timber modelling. The PhD program includes research-level courses suited to your individual needs during your research, and active participation in scientific conferences to build your network in the international research community in the field.

Duties The research area is multidisciplinary in nature and includes areas such as material science, physics, data science, image analysis, and production technology. The work comprises the development of AI and deep learning models that make it possible to extract comprehensive and quality-relevant information from CT data of wooden logs and boards in an automated manner.

Collaboration will be included with related projects, e.g. for the development of measurement methods, finite element modelling of CT data, material analysis, optimization of the value exchange, process optimization, and quality management.

All scientific work is presented in English in the form of peer-reviewed articles in scientific journals and at international conferences, which are the main evaluation criteria to complete the PhD studies. In addition, 25% of your PhD studies are dedicated to course work, of which the majority can be chosen according to your needs and interests. At the end of your studies, you will summarize your work in a PhD thesis and defend it in front of a scientific committee.

Qualifications Basic qualifications for postgraduate education have those who have: 1) completed a degree at advanced level 2) completed course requirements of at least 240 higher education credits, of which at least 60 higher education credits at advanced level, or 3) in some other way within or outside the country acquired mainly corresponding knowledge.

A suitable background is a university degree or otherwise certified expertise in computer science, data science, or a similar field. The applicant must have a clear interest in modelling, data analysis, experimental studies, and customary engineering issues. While not necessary, expertise in machine learning/deep learning, and the Python programming language (incl. PyTorch or Tensorflow/Keras) is appreciated. Even knowledge of finite element analysis and similar modelling approaches are of advantage. Knowledge of wood or material science is not necessary, but a merit if present.

The applicant must be a good team player with good knowledge of English, in both oral and written presentation. Knowledge of the Swedish language is not a requirement for the position, but the applicant should be able to perform tasks that require a basic understanding of Swedish in a few years' time.

We encourage applications from individuals who identify themselves as non- male.

For further information about the subject see; General curricula for the Board of the faculty of science and technology.

Further information Employment as a PhD student is limited to 4 years, teaching and other department duties may be added with max 20%.

For further information about the position, please contact: Professor Dick Sandberg, +46 910-58 53 71, [email protected] och Benedikt Neyses, +46 72-219 69 79, [email protected].

Union representatives: SACO-S Kjell Johansson (+46)920-49 1529 kjell.johanss[email protected] och OFR-S Lars Frisk, 0920-49 1792 [email protected].

In case of different interpretations of the English and Swedish versions of this announcement, the Swedish version takes precedence.

Application We prefer that you apply for this position by clicking on the apply button below. The application should include a CV, personal letter and copies of verified diplomas from high school and universities. Mark your application with the reference number below. Your application, including diplomas, must be written in English or Swedish.

Reference number: 3213-2023 Last day of application : 30 september 2023

From this employer

Recent blogs

Recent news