PhD student in Forest industrial production systems (Forestry digitalization), number: HR-2023/320;

Welcome to Linnaeus University! We meet the societal challenges of today and tomorrow in a spirit of openness, curiosity and creativity. By creating arenas for exchange of knowledge from different subjects, fields and cultures, we open up for new ideas and create new opportunities for long-term sustainable societal development. Linnaeus University – where people grow.

The Faculty of Technology offers a broad spectrum of activities across ten different departments and is central to the technical education and research conducted at Linnaeus University. The Department of Forestry and Wood Technology offers a wide-ranging of thematic activities from forest to finished wood products. Benefits for the climate arising from forests lie at the core of all department activities. To its growing team of forest scientists, the department is now looking for a highly motivated individual with a genuine interest in forest remote sensing.

The position will be linked to the Linnaeus University Centre for Data Intensive Sciences and Applications (DISA), focusing its efforts on scientific questions in collection, analysis, and utilization of large data sets. With its core in computer science, it takes a multidisciplinary approach and collaborates with researchers from all faculties at the university.

Subject area for the position: Forest industrial production systems. Location until further notice: Växjö

Term and hours: The doctoral studentship is limited in time in accordance with the Higher Education Ordinance (Chapter 5, Section 7). The studentship is full-time. The total employment period may not be longer than the equivalent full-time postgraduate studies of four years.

The Higher Education Ordinance states that anyone who is employed as a doctoral student shall primarily devote themselves to their own studies, although they may, to a limited extent, also work with education, research, and administration. Before a doctorate has been awarded, such work may not exceed 20% of full-time work.

Starting date: Starting date as soon as possible or as agreed upon.

Job description:

The PhD student will work with current and relevant challenges for society linked to the digitalisation of forestry within the forestry value chain. The PhD student project will contribute to developing new and improved estimates of forest variables (state and changes) as well as to mapping and forecasting forest damage for next-generation dynamic forest maps and forest management plans using remote sensing data in combination with field data.

The project will include the analysis of remote sensing data collected from instruments mounted on towers, drones, aircrafts, and satellites for the possibility of up-scaling to cover larger geographical areas. Field data will be collected to be used as reference data and include traditional forest measurements as well as tree physiology measurements, and data from harvesters.

Mainly radar data will be used, but data from laser and optical instruments will also be included as important data sources depending on the research application. An important part is to investigate how radar data can be used to measure forest water dynamics, which can be used to improve the estimation of forest variables and early detection of forest damage. The doctoral student is expected to be responsible for the practical fieldwork. Central parts of the work are writing and publishing both scientific articles and popular science articles as well as disseminating the research results.

 Furthermore, the PhD student will participate in both national and international projects and meetings. The PhD student will also collaborate with national and foreign experts in remote sensing. Since the studies generate large amounts of data, the doctoral student will also seek collaboration with the cutting-edge research environment DISA at the university.

Qualifications

A person fulfils the general entry requirements if she/he has:

  • Graduated at advanced level in the relevant field
  • Completed undergraduate program of at least 240 ECTS, including 60 ECTS at the advanced level, or the equivalent knowledge obtained in or outside of Sweden

Specific requirements

  • At least 90 ETCS in subjects relating to the proposed research subject or equivalent knowledge acquired in any other manner within or outside of Sweden
  • Good language skills in Swedish and/or English
  • Finally, it is required that applicants are judged to have the ability needed to complete the education

Other requirements

The successful applicant shows high motivation and interest in the research topic. The applicant must have a master’s degree (or equivalent) in a subject relevant to the position, such as forestry science, biology, technology, remote sensing and/or statistics. Proven communication skills in written and spoken English are important, as well as a good ability to work independently and in a group. A driver’s license is a requirement for the position.

Desirable qualifications

Theoretical knowledge and practical experience in forest remote sensing, forest inventory, forest damage, programming, statistical analysis, and knowledge of the Swedish language, are considered as merits.

Basis of assessment

Selection for postgraduate education is based on the assessed ability to cope with the demands of postgraduate education. The assessment of the ability is primarily based on the study results at the first level and advanced levels. The following aspects will be considered:

  • Knowledge and skills relevant to the topic of the project and the educational subject. These can be shown through the attached documents
  • Assessed ability to work independently and ability to formulate and approach scientific problems. The assessment can, for example, contemplate the degree project and a discussion about it during a possible interview
  • Ability for written and oral communication in English
  • Other experiences relevant to the education at the postgraduate level, e.g., professional experience

Consideration will also be given to good cooperation skills, independence and personal suitability, as well as how the applicant, through her/his experience and competence, is judged to have the ability needed to complete the postgraduate education.

Application procedure;

The application must contain:

  • A personal letter explaining why you are interested in the position and how the research project matches your interests and educational background
  • CV
  • Degree certificate or equivalent, a copy of the thesis or the equivalent, alternatively a summary if the work has not been completed
  • Other things you wish to refer to (copies of grades, information about references, letters of recommendation, etc.)
  • Completed application form

Further information

Head of Department Erika Olofsson, 0470-70 89 99, erika.olofsson@lnu.se

Main supervisor Professor Johan Fransson, 0470-76 70 42, johan.fransson@lnu.se

HR-partner Jesper Pettersson, 0470-70 89 99, jesper.pettersson@lnu.se

Welcome with your application according to instruction, last day to apply is 31 March 2023.  Linnaeus University has the ambition to utilize the qualities that an even gender distribution and diversity brings to the organization.

Please apply by clicking on the Apply button at the bottom of the ad. Applicants are requested to the application resolving CV, cover letter , a copy of a relevant essay , grades and certificates and other relevant documents. The applicant also requested to submit with their application a proposed research plan within the current area of research.

All documents must be attached to digital in the application. The application and other documents shall be marked with the reference number. All documents cited must be received by the University no later than 24.00 (Local time in Sweden) on the closing day.

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Postdoctoral position in Digitalization of Forestry with focus on forest remote sensing and planning:

Reference number: HR-2023/162

Welcome to Linnaeus University! We meet the societal challenges of today and tomorrow in a spirit of openness, curiosity and creativity. By creating arenas for exchange of knowledge from different subjects, fields and cultures, we open up for new ideas and create new opportunities for long-term sustainable societal development. Linnaeus University – where people grow.

The Faculty of Technology offers a broad spectrum of activities across ten different departments and is central to the technical education and research conducted at Linnaeus University. The Department of Forestry and Wood Technology offers a wide-ranging of thematic activities from forest to finished wood products. Benefits for the climate arising from forests lie at the core of all department activities.

The position will be linked to the FRAS II research program, jointly run by Linnaeus University, Skogforsk and the Swedish University of Agricultural Sciences in close cooperation with the forest sector in southern Sweden. The research program will consist of three PhD student projects and three postdoctoral projects that focus on different aspects of forest management.

It will also be linked to the Linnaeus University Centre for Data Intensive Sciences and Applications (DISA), focusing its efforts on scientific questions in collection, analysis, and utilization of large data sets. With its core in computer science, it takes a multidisciplinary approach and collaborates with researchers from all faculties at the university.

Subject area for the position: Digitalization in Forestry

Location until further notice: Växjö

Hours and term: Full-time for 2 years.

Starting date: Starting date as soon as possible or as agreed upon.

Job description: Forest management plans have long been used as a tool for individual forest owners to get an overview of the forest in order to plan forestry activities. The forest management plan has traditionally been produced with aerial photographs followed by field inspection.

As remote sensing data becomes more available, e.g. through satellites or national laser scanning, forest variable estimates from remote sensing can partly be used instead of field visits, which rationalized the production of the forest management plans. The forest owner has also increasingly been able to access the forest management plan digitally via the web to note, e.g. wind-thrown and insect damage forest. However, the forest management plan is mainly updated when a new plan is ordered.

This normally happens every 10 years, which is based on today’s certification requirements. It is, therefore, obvious that a more frequent updating of the forest management plan is required, where remote sensing can play an important role. Recent studies point to the need to use the forest management plan also as a surface for communication between the forestry operator and the forest owner.

There is a desire for a more interactive forest management plan, where several management options for each area or stand are presented. There are also a need to follow how the forest develops in the longer term in a changing climate. Increased possibilities exist today to automatically and continuously update the content of the forest management plan using time series of remote sensing data together with field data, e.g. from harvesters.

The postdoctoral project aims to scientifically produce new knowledge with the objective of developing the next generation’s digital and dynamic forest management plans. Initial work in the project includes mapping private forest owners’ own perceptions of the need for improved decision support in their forest management plans.

With this as a starting point, questions can be answered such as how the new need for information in future forest management plans can be met. An important part of the project is to study how today’s static plans can be developed into digital and dynamic forest management plans.

The position also includes responsibility for research communication, which means participating in national and international meetings. Publishing both popular science articles and scientific articles are central parts of the work.

The postdoctoral fellow is expected to participate actively in the department’s knowledge environment and networks, both internally and externally, as well as to develop new project ideas and participate in applying for external project funding. A certain amount of teaching and supervision at basic, advanced and/or postgraduate level may be included in the duties.

In addition to the mentor group, the postdoctoral fellow will collaborate with national and international experts in the field. For example, an opportunity is offered to collaborate with researchers in the Horizon 2020 project ForestMap, which aims to produce the next-generation forest maps with AI. Since the studies can generate large amounts of data, the postdoctoral fellow will also seek collaboration with the cutting-edge research environment DISA at the university.

Qualifications

Anyone who has a doctorate in forest management, forest remote sensing, forest planning, biology, technology or equivalent, or who has a degree from another country that is equivalent to a doctorate in the above subjects, qualifies for the position.

In accordance with the postdoctoral agreement, applicants who were awarded their degree no more than three years prior to the last application date for the present position should be considered first.

An applicant must not previously have been employed as a postdoctoral fellow for more than a year within the same or a related subject area at Linnaeus University.

In order to qualify for the present position, the applicant must also be able to demonstrate scientific skills in the subject area. The position also requires proven communication skills in written and spoken English, as well as good ability to work independently and in a group. Driving license is a requirement for the position.

Assessment criteria

Theoretical knowledge and practical experience of decision support systems, modelling, statistical analysis, programming, forest remote sensing, forest planning, forest inventory and forest damage with a bearing on Nordic forestry and knowledge of the Swedish language are meritorious. Good scientific publication rate and experience in applying for external project funding is desirable. The work takes place in a research group, which is why cooperation and flexibility are given great importance.

Documented experience of research in forest remote sensing and forest planning. In the overall assessment of the scientific skills, special emphasis is placed on the applicants’ potential for a successful career as a teacher and researcher.

When the university employs new teachers and researchers, the choice should fall on those applicants who, based on a qualitative holistic assessment of competence and skills, are considered most likely to successfully perform and develop relevant tasks and contribute to successful development of the organisation.

Contact:

Professor Johan Fransson, 0470-76 70 42, johan.fransson@lnu.se

Head of department, Erika Olofsson, 0470-70 89 99, erika.olofsson@lnu.se

HR-partner Jesper Pettersson, 0470-70 89 99, jesper.pettersson@lnu.se

Welcome with your application according to instruction, last day to apply is 31 March 2023. Linnaeus University has the ambition to utilize the qualities that an even gender distribution and diversity brings to the organization.

Please apply by clicking on the Apply button at the bottom of the ad. Your application should be designed according to the Template for application which can be found in the Guide to Appointment procedures under important documents below the ad.

The credentials you invoke must be verified with certification and they must be attached digitally in your application. Other documents, including various types of scientific works, must be submitted digitally along with the application. The application and other documents to be marked with the reference number. All documents cited must be received by the University no later than 24.00 (Local time in Sweden) on the closing day.

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