Course archive

Course archive

The course archive gives you information about some of the past doctoral courses that have been given at BTH. The purpose is that you have access to past course syllabi should you wish for a course to be given again or adapted into an individual study course by your supervisors or Examiner.

Research Funding, 3 hp

Course registration (BTH Inside)                         Course Descriptor


The aim of the course is to strengthen PhD student’s capabilities to apply for external funding of research projects. Corresponds to 3,0 credits (högskolepoäng) for doctoral students.

Target group

1) PhD students, preferably in their second half of doctoral studies

2) Post docs, if seats are available, are also welcomed.

In total 20 seats will be available.

Time and place

The course will be held during March 2023.  The course will have four seminars (particpation is mandatory):

  • Seminar 1:  03 March 09:00 – 12:00
  • Seminar 2:  09 March 09:00 – 16:00
  • Seminar 3:  16 March 09:00 – 12:00
  • Seminar 4:  28 March 09.00 – 16:00

As active interaction between participants during exercises and discussions are an important part of the course dynamics it will be given on site at BTH Karlskrona only. Between seminars participants will be given home exercises to be followed up during seminars. Specific venues will be published later on. 

Course content

The funding landscape, Strategies for grant applications, Time-frame for proposals, Budgeting for projects, Writing and presenting research funding proposals, Innovation aspects on research proposals, Open science including open access and open data


Register here. Last date to register is 20 January 2023. Please note that there are limited seats. If the course is full, we will put you on a waiting list.


  • Eva-Lisa Ahnström, BTH;
  • Marie Wik, BTH;
  • Annett Wolf, Linnéuniversitetet;
  • Tobias Larsson BTH;
  • Kennet Henningsson, BTH,
  • Kent Adolfsson, BTH.
  • Also, representatives from financing bodies and other specialists will give presentations, tbc.

Information retrieval for PhD students

The course “Information Retrieval for PhD students” is open for registration. The aim of the course is to develop the participant´s information literacy, which will say, the ability to search, critically evaluate and use information during the process of writing the thesis.


The following main topics will be dealt with during the course:

  • Search Strategies
  • Information Retrieval
  • Information Sources
  • Scholarly Communication
  • Open Access
  • Bibliometrics
  • Research Data
  • Reference Management
  • Systematic/Literature Reviews
  • Literature Monitoring
  • Internet and the Visible Researcher

The course is web-based with some compulsory lectures. Participants should independently find their way to an individual search and publishing strategy within their research area by finding and reading relevant literature, working with exercises, writing compulsory assignments and reviewing the work of others. The course organization requires active participation. At the examination, which is mandatory and on campus (or online via zoom), the students will present their thesis and review someone else’s work.

Course start

The course starts week 44 2022 and continues to week 2 2023. There are 10 sessions planned, once a week on Wednesday afternoons (if you prefer another day we can always discuss that)

The sessions are an opportunity for you to understand and discuss the assignments and exercises and get feedback on your findings and your work. Almost every week during the course you need to hand in an assignment no later than Monday the same week.

In the first session, we will introduce ourselves, the course content, literature and the learning platform. We will discuss searches and the concept of information literacy. We want you to present yourself, your research area and what you expect from the course. Also, consider how you would describe your research topic with a few keywords.


Innovation and entrepreneurship

The innovation office at BTH is giving a PhD course in Innovation and entrepreneurship during the spring of 2023. The course aims to support researchers in the process of taking research results to Innovation, impact and commercialization. The course is divided into two parts of 2 credits each, where the second part is optional.

Part one: The first part consists of four seminars covering areas of IPR, capital raising, business modelling, timing, team building and internationalisation. Each seminar includes both preparations and reflections. The preparations and reflections are conducted individually and could be either a written submission or an oral presentation. (2 credits)

Part two (optional): For 2 additional credits, the student is required to submit a written business plan (optional topic) and participating in presentation and pitching. Coaching is included individually and/or in group. (2 credits)

  1. The course is planned in lp 4, i.e., second part of the spring 2023.
  2. The course is provided by Innovation office at BTH in cooperation with external expert representatives who will give seminars.
  3. Other senior researchers are also welcome to attend and follow the seminars.

Philosophy and Methodology of Applied Sciences 

The aim for the doctoral student is to acquire knowledge and develop skills in the area of philosophy of
science and methodology of applied science. It aims to increase the students’ ability to formulate and
applied scientific principles within their own area of research.


PART 1: Theory/Seminars, 3 ECTS credits
− History of science: from experience facts to experimentalism;
− Modern theory of science: falsificationism, Kuhn’s paradigm, Lakato’s research programmes,
Feyerabend’s anarchistic theory of science, subjective Bayesians, and new experimentalism;
− Methodology of applied science;
− Legal and ethical aspects of publishing.
PART 2: Project/Workshops, 4.5 ECTS credits
− Approaching research problem – a research question and hypothesis;
− Validation and verification of research hypothesis;
− How to organise and write thesis and scientific paper;
− Tools for referencing and using templates.
− Presenting and disputing of research results;
− Reviewing of the research reports;
− Project and team work management.


Knowledge and Understanding
− fundamental concept and theory concerning modern paradigm in science, special in applied
− Academic and publishing culture.
Skills and Abilities
− Scientific writing;
− Research competence;
− Write, present and dispute scientific papers and reports.
Judgment and Approach
− Be able to analyse, review and oppose scientific papers and reports.

The examination consists of active compulsory participation in seminars and workshops, written
assignments submitted and presented in different ways.
Code Module Credit
Theory 3.0 ECTS
Project – individual part 2.0 ECTS
Project – group part 2.5 ECTS
Assessment of the course is the grade pass or fail (G/U).

Course literature and other teaching material

− A.F. Chalmers: What is this Thing Called Science? ISBN 0-87220-452-9.
− Course coordinator will provide suitable compendia and a list of supplementary literature before
the course starts

Industry-academia co-production

Corresponds to 3 higher education credits (högskolepoäng)

The aim is for the doctoral student to acquire advanced knowledge and skills in the industry-academia co-production. The course will discuss the following aspects:

  • Introduction to the process of co-production between industry and academia.
  • The main phases and steps involved in the process.
  • Role descriptions for the main actors involved in the process.
  • Knowledge dissemination and reporting.

 The objectives regarding knowledge and understanding include

  • In-depth knowledge of industry-academia co-production

 Skills and Abilities

  • Ability to plan and execute research in co-production with industry partners.

Course literature and other teaching material

  • Gorschek T., Wnuk K. (2020) Third Generation Industrial Co-production in Software Engineering. In: Felderer M., Travassos G. (eds) Contemporary Empirical Methods in Software Engineering. Springer, Cham.
  • Gorschek, P. Garre, S. Larsson and C. Wohlin, “A Model for Technology Transfer in Practice,” in IEEE Software, vol. 23, no. 6, pp. 88-95, Nov.-Dec. 2006, doi: 10.1109/MS.2006.147.

Reading and Reviewing Research Papers

Third-cycle course

Corresponds to 5 higher education credits (högskolepoäng)

The objective of this course is to support doctoral students at BTH in the process of reading and reviewing academic work (conference, workshop, and journal publications). Moreover, the goal is to learn the students how to write good rejoinders of their own papers and work with reviewers and editors of academic conferences and journals.

The course includes five seminars where different aspects of reading, reviewing, and preparing a rejoinder are discussed and examples are provided. Moreover, the course contains two assignments where students show the ability to review a research paper and prepare a rejoinder to a research paper.

 Knowledge and understanding

  • Knowledge and understanding of the review process in academia
  • Knowledge and understanding of the rebuttal process in academia


Skills and Abilities

  • Ability to time-efficiently read research articles
  • Ability to time-efficiently review an assigned paper and prepare constructive comments
  • Ability to prepare a good rejoinder and address the reviewers’ comments on your own submissions
  • Ability to critically review your own research articles

Judgement and approach

  • Judge the effort and strategies needed for writing a good rejoinder
  • Judge the effort required when acting as a reviewer to a paper and the expected level of feedback

The teacher provides the necessary literature during the seminars

Modern Methods of Statistical Analysis and Estimation, 7,5 hp

During the winter 2018/2019, The Department of Mathematics and Natural Sciences gave a statistics course for Ph.D. students in Mathematics and Engineering sciences. The course (7.5 hp) consists of the following areas:

  • Estimation in general
  • Regression analysis (including multiple and non-linear regression)
  • Analysis of variance (ANOVA) with application to planning of experiments
  • Non-parametric methods (Methods which can be used when the data are not Gaussian distributed)
  • Time series analysis including ARMA models (very applicable in signal processing and prediction in general, e.g. in economy)
  • Orientation about random processes (applicable in e.g. reliability and telecommunications)
  • Computer labs using the software SPSS and R


Textbook: Walpole, R.E. et al (2011 or later). Probability and statistics for engineers and scientists. Pearson Education.

Additional documents from the Department of Mathematics and Natural Sciences.


Prerequisite: a basic course in probability and statistics (at least 6hp).

Sustainability in Engineering Product Development, 20 hp

A product development PhD Course suite of 20 hp in total, including four independent modules of 5 hp each.

(1) A Critical Review of the Product Development Process (PDP), 5 hec

(2) Sustainability in Engineering Product Development (SEPD), 5 hec

(3) Modeling, Simulation and Optimization (MSO), 5 hec

(4) Engineering Innovation and Management (EIM), 5 hec

This suite is recommended for PhD candidates in Engineering Product Development and the modules are given for the first time during 2016-2017

More information

Computer Vision by learning, 7,5 hp

The use of enormous computing processing power in combination with ease of accessing the network resources was a dream for twenty or even ten years ago. Thanks to these achievements we see today hundreds of applications pops up every day. Many of them implement computer vision learning algorithms on images, videos or 3D contents for object and pattern recognition, structural prediction, semantic content segmentation and tracking as some examples.

Course descriptor

Modeling Simulation and Optimization in the Engineering Product Development Process, 5 hp

The course aims to provide a basic understanding for how modelling, simulation and optimization can be employed to support the product development process

Course website and more information

Research Ethics in Computing and Engineering, 3,0 credits

The aim is for the doctoral student to acquire awareness, knowledge and capability to conduct research taking different ethical aspects into account. Content − Introduction to research ethics (seminar and discussions), − Focused study on a selected topic on research ethics (report and presentation), − Insights into different topics related to research ethics (seminar and discussions)

Course descriptor

Scientific Communication I and II, 2 hp

Course descriptor


The main objective of the course is to teach the candidates to communicate scientific ideas and results both to academic audiences and to the public in general. The first part of the course (Scientific Communication I) will focus on the popular science format, while the second part (Scientific Communication II) will focus on the academic format. The course will give practical experience with presenting own ideas, as well as receiving feedback and critically reviewing others’ work.


The course will be organized around a set of seminars and workshops with candidate presentations.

  • Scientific Communication I – Popular science presentations
    • Seminar I:
      • Public understanding of science and dialog with society.
      • Formats and style. Storytelling. Popular science magazine articles and general press.
    • Seminar 2:
      • Presenting research ideas and results to public.
      • Formats and style. Elevator pitches, TED talks.
    • PhD Workshop
      • Candidates prepare a presentation of their ideas and results and give a presentation in an annual PhD workshop
  • Scientific Communication I – Academic presentations
    • Seminar 1:
      • Communicating scientific ideas and research to an academic audience. Format and style
    • Seminar 2
      • Scientific reviews. Providing and receiving constructive feedback.
    • PhD Workshop
    • Candidates prepare an extended of their ideas and results and give a presentation in an annual PhD workshop

Computer Vision by Learning, 7,5 hp

The course may be given as a 3,0 hp (assignments) + 4,5 hp (project) course 

In recent years, learning has become a dominant classification tool for a variety of domains. In computer vision, the tools have been used to promote object and pattern recognition, which have proven to be very successful. In this course we will study learning methods for various computer vision problems. In these methods either invariant features are detected and implemented in the learning process or simply original images/videos are used.

With this background, the course aims to provide students with insight into the fundamentals of advanced subjects in computer vision using learning methods.


Central items of the course are:

  • Overview of image segmentation and object detection
  • Modeling concept vice versa learning concept
  • Invariant features
  • Learning using invariant features
  • Deep learning for pattern recognition
  • Structural Prediction
  • Semantic image segmentation with deep learning
  • Tracking and event recognition with deep learning

Recommended prerequisites: Linear algebra and Programming

Course descriptor

Research Ethics, 3 hp

Course descriptor


The main objective of the course is to raise awareness and knowledge about the various aspects related to research ethics and misconduct.

Content and tentative schedule

The course will be organized around a set of seminars and conclude with a workshop with participant presentations.

  • Seminar I [2020-10-01 9:00-11:00]: Introduction to research ethics.
  • Seminar 2 and Groupwork [2020-10-08 9:00-11:00]: Data handling.
  • Seminar 3 [2020-10-15 9:00-11:00]: Scientific authorship and scientific publishing.
  • Seminar 4 [2020-10-22 9:00-11:00]: Research misconduct.
  • Workshop [2020-11-19 9:00-12:00]: Students presentations (additional workshops might be booked depending on the number of course participants)

Note: The course is likely to be run on a distance.

Innovation and entrepreneurship with research perspective - part 1, 2 hp

The main objective of the course is to support researchers in their process of taking research result to innovation, impact and commercialization. This is conducted through providing seminars on intellectual properties, economy, business modelling along with working through cases, own or provided.
The course is organized around a set of seminars and assignments. The assignments are conducted individually and could be delivered either written or orally.
Knowledge and understanding
On the completion of the course, the student will be able to:

Demonstrate insight to the various steps in an innovation and entrepreneurial process, specifically from a research perspective.

Demonstrate orientation about the different pathways utilization of research.
Competence and skills
On completion of the course, the student will be able to:

Complete a Business Model Canvas for a given project idea. The project idea should be based on research (hypothetical research or ongoing research).

Course Descriptor

Innovation and entrepreneurship with research perspective part 2, 2 hp

The main objective of the course is to assist researchers to develop a business plan to attract
potential investors in the process of taking their research results into innovation, impact and
commercialization , and also to
The course is organized around a number of seminars and coaching sessions, individually
and/or in smaller groups. The course will conclude with a workshop presenting and
discussing developed material, and also pitching a potential business idea.
Knowledge and understanding
On the completion of the course, the student will be able to:

Demonstrate insight to parts of a business plan and the process of developing a business plan.

Demonstrate insight towards the possible investment alternatives for funding a start-up business.
Competence and skills
On the completion of the course, the student will be able to:
Complete a written business plan based on a given project idea. The project idea should be based on research (hypothetical research or ongoing research).
Develop investment package, first version, intended for equity investment.
Skills in pitching a business plan.

Course Descriptor