Decisions and guidelines

The deciding board is the Undergraduate and Master's Education Committee at the Faculty of Medicine

Entry requirements

Academic requirements:

A Bachelor's degree, equivalent to a Swedish Kandidatexamen, from an internationally recognised university. The degree must be in biochemistry/chemistry, biology, biomedicine/medicine, biotechnology, bioinformatics, cell-/molecular biology, genetics, life science, medical sciences, pharmacy, or a similar field of study.

Also required is:

• courses in biochemistry, cell biology, bioinformatics, chemistry, genetics, and molecular biology/-genetics totalling at least 30 credits; and
• courses in statistics, mathematics, or computational science totalling at least 5 credits.

Language requirements:

Proficiency in English equivalent to the Swedish upper secondary course English 6. This requirement can be met either by achieving the required score on an internationally recognised test, or by previous upper secondary or university studies in some countries. Detailed instructions on how to provide evidence of your English proficiency are available at universityadmissions.se.

Aims

The education will give knowledge and qualifications for a profession in the health care, in industry or for education at doctoral level. After the education, the student should be able to participate in research, development, and investigation work in medical areas where a data-driven methodology is used and where large-scale health-related data is generated, used and analysed in relation to precision medicine research or in clinical routine.

Learning outcomes

For the Master's degree, the student must fulfil the objectives specified in the Higher Education Ordinance's (1993: 100) System of Qualification. Within the scope of the aims that are stated in the Higher Education Ordinance, the student should after completed education in the Master's (120 credits) programme in precision medicine satisfy the following locally determined aims:

• be able to summarise the knowledge situation in precision medicine and other adjacent fields in life sciences where similar methodology is used regarding study design, analytical methods, interpretation of results and applications in health care.
• have acquired a good overview of how their own knowledge and skills can contribute to solve different assignments in academia, health care, industry and in the society
• have advanced theoretical and practical knowledge of analytical methods and research methodology in the field. This includes knowledge of human genetics, cancer genomics and molecular medicine as well as technologies and methods for analysing e.g. DNA, RNA or protein in different tissues.
• master different computer-based analytical methods such as bioinformatics and biostatistical analyses as well as methods in machine learning and artificial intelligence. This also includes interpretation and visualization of the results relative to a defined outcome, e.g. disease or risk of disease.
• be able to independently choose the optimal molecular technology and computer-based analysis method in relation to a given question in health care.
• be able to independently take responsibility for, and lead, studies on a scientific basis and evaluate and report results from these studies.
• demonstrate knowledge of relevant laws and regulations that regulate ethical issues in the field and obtain practical knowledge in handling sensitive human data in a secure manner.
• be able to collaborate effectively with others in the team and with different partners in health care, industry or academia. 

Layout of the programme

The courses are based on prior knowledge in genetics, cell and molecular biology, and basic statistics from the bachelor's level. Furthermore, the student is expected to work with a high degree of independence and take responsibility for their own learning. Progression within the program is ensured through prerequisites and overall planning where later courses deepen and develop knowledge from previous courses within the program. Students who do not choose an advanced degree project of 45 credits, will instead complement a degree project of 30 credits with elective courses corresponding to 15 credits. These elective courses can be chosen as specialization within or outside the main field of study or broadening courses before the degree project starts.

1st semester

Medical Genetics and Cancer - Molecular Mechanisms, 15 credits (main field of study: Molecular medicine)

Introduction to R, 7.5 credits  (main field of study: Statistics)

Biostatistics, 7.5 credits  (main field of study: Statistics)

2nd semester

Molecular Techniques and Data Analysis in Precision Medicine I, 7.5 credits (main field of study: Precision medicine)

Introduction to machine learning and artificial intelligence for life sciences, 7.5 credits (main field of study: Precision medicine)

Molecular Techniques and Data Analysis in Precision Medicine II, 15 credits (main field of study: Precision medicine)

3rd semester

Applied Precision Medicine, 15 credits (main field of study: Precision medicine)

Elective course(s), 15 credits, or 45 credits degree project 

4th semester

Degree project, 30 credits, or 45 credits (main field of study: Precision medicine)

Instruction

Throughout the programme, studies are schedule-based with the teaching activities consisting mainly of lectures, seminars and group or individual assignments. Laboratory exercises, study visits and demonstrations can also occur.

Degree

The program leads to a Master's degree in medicine (Master of Medical Science, 120 credits) with precision medicine as the main field of study.