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Master's Programme in Life Science Technologies
Curriculum 2024-2026
About the programme
Master's Programme in Life Science Technologies offers a multidisciplinary curriculum focusing on important aspects of current and emerging technologies for life sciences, covering fields such as biological data analysis and modeling, advanced biomaterials and bioelectronics, biomedical engineering and neuroscience. The programme draws on fundamental and applied knowledge on these fields, and is closely linked to research conducted in the participating schools and departments.
To prepare the graduates for their future work with large and often complex systems, the programme includes practical project works in groups, which provide skills for solving multifaceted and ill-defined problems similar to those faced in the actual professional life. These projects typically include experimental and practical components as well as fundamental theoretical aspects.
The programme also gives the student a comprehensive foundation for doctoral studies.
After graduation students of Life Science Technologies programme
- will have relevant fundamental and applied knowledge and competencies within the specialization area as well as a good overview of current and emerging technologies and methodologies in the field of life sciences.
- will have the necessary skills to develop innovative scientific and engineering solutions for health and wellbeing sectors, acknowledging the importance of responsible use of technology.
- will be able to plan and execute research in life science, analyze data and report the outcomes both orally and in writing to different stakeholders
- will have a solid foundation for further learning of professional skills by acquiring, evaluating, and processing scientific, technical and professional information.
- will be able to work individually or as a member of a multidisciplinary expert team.
Six majors with different focus are offered in the Master's Programme in Life Science Technologies:
Bioinformatics and Digital Health
The Bioinformatics and Digital Health major gives a strong competence in bioinformatics and computational methods for analyzing various biomedical and health data. The major offers a strong background in probabilistic modeling, machine learning, data science and artificial intelligence to understand the methodological basis of bioinformatics and computational biology methods. Students graduating from this major have excellent skills to start their careers in fields intersecting life science and data science.
Biomedical Engineering
Biomedical Engineering builds on physics, data science, and technology to observe and influence biological systems. This major introduces the student to key constructs in biological systems, physiological and physical signal generation therein, and the measurement and analysis of these signals. In addition, the major provides knowledge and skills for developing novel engineering solutions for diagnostic and treatment needs in health care. Biomedical Engineering major offers excellent foundations for pursuing a career in life science and medical technology industries as well as in academia.
Biosensing and Bioelectronics
The aim of Biosensing and Bioelectronics major is to educate engineering specialists with a comprehensive grasp of detecting, processing, and analyzing biosignals from various origins. To attain this goal, students delve into a broad spectrum of subjects, encompassing nanoscale phenomena, microfabrication techniques, biomaterials interfaces, biochemical recognition of biomolecules, physical transducers, sensor technologies, and a comprehensive overview of diverse clinical equipment. Foundational knowledge crucial for propelling innovations in biosensors and bioanalytics is imparted. Furthermore, students are strongly urged to merge practical considerations and explore potential applications of their expertise throughout their academic journey. This program seamlessly blends theoretical and practical studies essential for conceiving, developing, fabricating, and characterizing biosensors, biomedical devices, and medical instruments.
Biosystems and Biomaerials Engineering
Biosystems and Biomaterials Engineering is designed to give graduates broad training and in-depth knowledge, combined with practical experience. The major offers three distinct tracks that link biosciences with information technology, chemistry or biomaterials allowing students to work at the interfaces of these different fields.
Complex Systems
The Complex Systems major gives a strong computational and theoretical background for understanding complex systems, from the human brain to a diversity of biological and social systems. The major offers three focus areas that students can choose from and build a major that contains the fundamentals of complex systems and a number of neuroscience courses, or a combination of network science and machine learning, or a more mathematical networks track including courses from the department of mathematics.
Human Neuroscience and Technology
The Human Neuroscience and Technology major provides students with a strong background in the structure and function of the human brain while having an emphasis on the theoretical and practical aspects of brain-imaging methods and other neurotechnologies. This major gives working knowledge on neural signalling, sensory systems, cognitive functions as well as on the application of brain imaging to study the human brain, including the analysis of the measured signals. Students graduating from this major are well equipped to pursue diverse careers in life sciences, data science and medical technology as well as to continue in academia.
Major 60 or 65 ECTS
Code: SCI3092
Extent : 60 ECTS
Abbreviation: BIOINFO
Professor in charge: Harri Lähdesmäki
Content description
The Bioinformatics and Digital Health major in the Life Science Technologies programme is designed to give a strong competence in bioinformatics and biomedical/health data analysis methods. The major offers a solid background in probabilistic modeling, machine learning and data science to understand the methodological basis of bioinformatics and computational biology methods. The major also gives skills and tools to develop new computational methods and models and to apply them to real world biomolecular and health data. Computer practicals are part of most courses ensuring understanding of both theory and practice of the methods.
State-of-the-art methods for analyzing various 'omics data as well as biological networks are part of the curriculum. Examples of research questions studied include predicting drug-target interactions, reconstructing biological networks, identifying disease biomarkers from biomedical and health data, and modelling dynamical behavior of complex biological systems.
Intended learning outcomes
After graduating from the Bioinformatics and Digital Health major students
- Will have a strong methodological understanding of computational and probabilistic techniques that are commonly used to analyze biomedical and health data
- Will be able to apply existing computational methods in challenging real problems
- Will have the knowledge to develop new computational methods for new applications
- Will be able to communicate the methods and findings to both computational and non-computational experts
Code | Course name | ECTS credits | Period/Year |
---|---|---|---|
JOIN-E3100 | Life Science Technologies Project Course A | 2 | I/1 |
JOIN-E3200 | Life Science Technologies Project Course B | 8 | III-V/1 |
Choose courses from themes 1 and 2 as is instructed. |
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Theme 1: Bioinformatics and digital healthChoose minimum of 15 ECTS. |
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CS-C4100 | Digital Health and Human Behavior | 5 | II/1 |
CS-E5875 | High-throughput Bioinformatics | 5 | III/1 |
CS-E5885 | Modeling Biological Networks | 5 | II/1 |
CS-E4885 | Machine Learning in Biomedicine | 5 | I-II/2 |
CHEM-E8120 | Cell Biology | 5 | I/1 |
Theme 2: Probabilistic modeling and machine learningChoose minimum of 15 ECTS |
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CS-E4715 | Supervised Machine Learning | 5 | I-II/1 |
CS-E5710 | Bayesian Data Analysis | 5 | I-II/1 or 2 |
CS-E4890 | Deep Learning | 5 | III-IV/1 |
CS-E4891 | Deep Generative Models | 5 | IV-V/1 |
CS-E4825 | Probabilistic Machine Learning | 5 | III-IV/1 |
CS-E4840 | Information Visualization | 5 | IV/1 |
CS-E4895 | Gaussian Processes | 5 | IV-V/1 |
Choose courses from the below list to fulfil the 60 ECTS requirement. |
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CS-E3190 | Principles of Algorithmic Techniques | 5 | I-II/1 |
CS-E4800 | Artificial Intelligence | 5 | III-IV/1 |
CS-E5795 | Computational Methods in Stochastics | 5 | I-II/1 or 2 |
NBE-E4150 | DNA Nanotechnology | 5 | I-II/1 or 2 |
NBE-E4305 | Biodesign–innovating medical technologies in multidisciplinary teams | 5 | V/1 |
TU-E5050 | HealthTech Linkage | 10 | III-IV/1 |
MS-E2112 | Multivariate Statistical Analysis | 5 | III-IV/1 |
CS-E4875* | Research Project in Machine Learning, Data Science and Artificial Intelligence* | 5-10 | I-V, summer/1 |
*The course is organised only in 2024-2025
Code: SCI3059
Scope: 65 ECTS
Abbreviation: BME
Professor in charge: Matias Palva
Content description
Biomedical engineering builds on physics, data science, and technology to observe and influence biological systems. This major introduces the student to key constructs in biological systems, physiological and physical signal generation therein, and the measurement and analysis of these signals. In addition, the major provides knowledge and skills for developing novel engineering solutions for diagnostic and treatment needs in health care. Biomedical Engineering major offers excellent foundations for pursuing a career in life science and medical technology industries as well as in academia.
Intended learning outcomes
After completing the Biomedical Engineering major, the students should be able to:
- Demonstrate understanding of the biology-, physiology-, and physics-based foundations of systems relevant for biomedical engineering,
- Exhibit understanding of the generative mechanisms and measurement methods of biological signals and approaches for manipulation of biological systems,
- Apply data pre-processing and analysis methods on empirical biomedical data with understanding of how they operationalize the underlying constructs,
- Apply or understand computational modeling methods for simulating the biomedical systems of interest,
- Understand the prospects and limitations of informatics and machine learning methods to biomedical data as a foundation for medical devices and applications,
- Create, evaluate, or analyze biomedical applications in their clinical and regulatory context.
Code | Course name | ECTS | Period/Year |
---|---|---|---|
JOIN-E3100 | Life Science Technologies Project Course A | 2 | I/1 |
JOIN-E3200 | Life Science Technologies Project Course B | 8 | III-V/1 |
NBE-E4070 | Basics of Biomedical Data Analysis | 5 | I-II/1 |
NBE-E4600** | Special Assignment** | 10 | I-summer/1 |
Choose courses from themes 1, 2 and 3 as is instructed. If needed, choose courses from group "other courses" to fulfil the 65 ECTS requirement. |
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Theme 1: Foundations in physiology and physicsChoose at least 10 ECTS. |
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NBE-E4100 | Molecular Biophysics | 5 | III-V O* |
NBE-E4120 | Cellular Electrophysiology | 5 | I-II E* |
NBE-E4210 | Structure and Operation of the Human Brain | 5 | I-II/1 or 2 |
NBE-E4060 | Bioelectromagnetism: Fundamentals, Modelling and Application | 5 | I-II/ 2 or 1 |
Theme 2: Measurement, manipulation, modeling, and analysisChoose at least 10 ECTS. |
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NBE-E4010 | Medical Image Analysis | 5 | I-II / 1 or 2 |
NBE-E4020 | Medical Imaging | 5 | III-IV E* |
NBE-E4045 | Functional Brain Imaging | 5 | I-II/2 |
NBE-E4250 | Mapping, Decoding and Modeling the Human Brain | 5 | III/ O* |
NBE-E4260 | Genesis and Analysis of Brain Signals | 5 | III-IV/1 |
NBE-E4310 | Biomedical Ultrasonics | 5 | I-II O* |
NBE-E4150 | DNA Nanotechnology | 5 | I-II/2 |
Theme 3: Informatics and applicationsChoose at least 5 ECTS. |
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NBE-E4080 | Decision Support in Healthcare | 5 | II/1 or 2 |
NBE-E4085 | Behavioral Health Informatics | 5 | IV/1 |
NBE-E4300 | Medical Device Innovation | 5 | III-V/1 |
NBE-E4305 | Biodesign — Innovating Medical Technologies in Multidisciplinary Teams | 5 | V/1 |
TU-E5050 | HealthTech Linkage | 10 | III-IV/1 |
Other coursesChoose courses to fulfil the 65 ECTS requirement, if needed. |
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NBE-E4130 | Information Processing in Neural Circuits | 5 | III-V O* |
NBE-E4140 | Neurophysics | 5 | IV-V E* |
ELEC-E8739 | AI in health technologies | 5 | I-II/1 or 2 |
NBE-E4540*** | Special Course in Biomedical Engineering*** | 2-5 | 1 or 2 |
E = lectured in even years
O = lectured in odd years
** The Special Assigment should be done before starting writing the master's thesis.
***The course is organized occasionally, not necessarily each year.
Code: ELEC3045
Scope: 60 ECTS
Professori in charge: Tomi Laurila
Professors: Mervi Paulasto-Kröckel, Ilkka Tittonen, Simo Särkkä, Ilkka Laakso, Ivan Vujaklijan, Philip Elvander
Content description
The objective is to cultivate engineering experts with a versatile understanding of detecting, processing, and analyzing biosignals from diverse sources. To achieve this, students are exposed to a range of subjects, including nanoscale phenomena, microfabrication techniques, biomaterials science, biochemical recognition of biomolecules, physical transducers, sensor technologies, and a substantial overview of various clinical equipment. Essential knowledge required for advancing innovations in biosensors and bioelectronics is provided. Additionally, students are strongly encouraged to integrate practical considerations and explore potential applications of their expertise throughout their academic journey.
This program seamlessly integrates theoretical and practical studies necessary for the conception, development, fabrication, and characterization of biosensors, biomedical devices, and medical instruments. Through hands-on experiences, students gain insights into the biocompatibility of both organic and inorganic materials used in electronics. Moreover, they delve into understanding the interactions between low-frequency electromagnetic fields and living tissues, including specialized applications involving single cells and biomolecules.
Intended learning outcomes
After completing the major students should be able to:
- Demonstrate recall and recognition of key principles in nanoscale phenomena, microfabrication techniques, biomaterials science, biochemical recognition, physical transducers, and sensor technologies related to biosensors and bioelectronics.
- Exhibit a comprehensive understanding of theoretical concepts related to the design, development, fabrication, and characterization of biosensors, biomedical devices, and medical instrumentations.
- Apply knowledge in practical settings, gaining hands-on experience in designing, developing, fabricating, and characterizing biosensors and related devices.
- Analyze and evaluate the effectiveness of sensor technologies in detecting and processing biosignals, considering practical aspects, biocompatibility, and interactions with living tissues, including specialized applications involving single cells and biomolecules.
Code | Course name | ECTS | Period/Year |
---|---|---|---|
JOIN-E3100 | Life Science Technologies Project Course A | 2 | I/1 |
JOIN-E3200 | Life Science Technologies Project Course B | 8 | III-V/1 |
ELEC-E8729 | Biomaterial Interfaces | 5 | I-II/1 |
ELEC-E8726 | Biosensing | 5 | III-IV/1 |
ELEC-E3261 | Characterization of Biomolecules | 5 | I/1 |
ELEC-E8734 | Biomedical Instrumentation | 5 | II/1 |
Choose courses from the below lists to fulfil the 60 ECTS requirement.You can choose courses from one or several themes. |
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Theme 1: Signal processing in biosciences |
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ELEC-E8739 | AI in health technologies | 5 | I-II/1 or 2 |
ELEC-E9111 | Mathematical Computing | 5 | I-II/1 or 2 |
CS-E4715 | Supervised Machine Learning | 5 | I-II/1 or 2 |
ELEC-E8743 | Neurorobotics | 5 | III/1 |
ELEC-E8744 | Electromagnetic field safety | 5 | III-IV/1 |
ELEC-E8740 | Basics of Sensor Fusion | 5 | I-II/1 or 2 |
Theme 2: Micro- and nanofabrication |
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CHEM-E5115 | Microfabrication | 5 | IV-V/1 |
CHEM-E8135 | Microfluidics and BioMEMS | 5 | III-IV/1 |
ELEC-E3280 | Micronova Laboratory Course | 5 | I-II/1 or 2 |
ELEC-E3220 | Semiconductor Devices | 5 | III/1 |
NBE-E4150 | DNA Nanotechnology | 5 | I-II/1 or 2 |
NBE-E4100 | Molecular Biophysics | 5 | III-V O* |
Theme 3: Biomaterials and electrochemistry |
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CHEM-E2155 | Biopolymers | 5 | III-IV/1 |
ELEC-E8725 | Methods of Bioadaptive Technology | 5 | I-II/1 or 2 |
CHEM-E4106 | Electrochemistry P | 5 | III/1 |
NBE-E4150 | DNA Nanotechnology | 5 | I-II/1 or 2 |
NBE-E4100 | Molecular Biophysics | 5 | III-IV O* |
Other courses |
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ELEC-E0210 | Master's Thesis Process | 2 | I - summer/2 |
NBE-E4305 | Biodesign–innovating medical technologies in multidisciplinary teams | 5 | V/1 |
* lectured in odd years
Code: CHEM3028
Scope: 60 ECTS
Professor in charge: Heli Viskari
Content description
The major in Biosystems and Biomaterials Engineering in the Life Science Technologies programme is designed to give graduates broad training and in-depth knowledge, combined with practical experience. Starting from the understanding of basic biological phenomena, three distinct tracks are offered that link biosciences with information technology, chemistry or biomaterials allowing students to work at the interfaces of these different fields. By using problem-based learning, the major supports the developments of skills and tools for solving the complex problems encountered within the fast-changing field of life sciences. Furthermore, the major supports the development of transferable skills such as organizing personal and teamwork, working as part of a team, and effective communication of scientific knowledge to a forum of peers and experts and to the general public.
Intended learning outcomes
After graduating from the Biosystems and Biomaterials Engineering major, the students:
- have an in depth understanding of cellular systems at the molecular and cellular level and possess basic experimental skills to genetically modify and analyse pro- and eukaryotic cells
- understand statistical methods and can apply them to real-world problems
- can work alone and in teams on multi-dimensional problems and communicate findings in oral and written form.
Students of Biosystems Engineering track
- gain deep knowledge on the engineering of cellular systems using genetic engineering and synthetic biology tools for designing of genetic circuits and cellular pathways
- can develop and apply computational methods for analysis of biological high-throughput data and understand the underlying statistical and computational concepts
Students in the Chemistry of Life track
- demonstrate a broad knowledge of the fundamental concepts of organic chemistry and biology
- understand the reactivity of small organic building blocks, can design synthesis reactions accordingly and analyse their structures
- understand how biological means can support synthesis of organic molecules
Students in the Biomaterials track
- understand the theoretical framework for the synthesis of synthetic and biopolymers using chemistry, enzymes or cells and can identify suitable methods for their charaterization
- understand the molecular level phenomena and biophysical properties of materials and their implications on biomedical applications
Code | Course name | ECTS | Period/Year |
---|---|---|---|
JOIN-E3100 | Life Science Technologies Project Course A | 2 | I / 1 |
JOIN-E3200 | Life Science Technologies Project Course B | 8 | III-V / 1 |
CHEM-E3190 | Metabolism D | 5 | I / 1 |
CHEM-E8110 | Laboratory Course in Biosystems and Biomaterials Engineering | 5 | I-II / 1 |
CHEM-E8120 | Cell Biology D | 5 | I / 1 |
MS-C1620* | Statistical Inference* | 5 | III-IV / 1 |
Choose one of the following tracks. |
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Track 1: Biosystems Engineering |
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CS-E5885 | Modeling Biological Networks | 5 | II/1 |
CS-E5875 | High-throughput Bioinformatics | 5 | III / 1 |
CHEM-E3111 | Cell Engineering | 5 | II / 1 or 2 |
CHEM-E8125 | Synthetic Biology | 5 | IV-V / 1 |
Select two of the following courses: | |||
NBE-E4150 | DNA Nanotechnology | 5 | I-II/2 |
CHEM-E3121 | Microbial Physiology D | 5 | II / 1 or 2 |
CHEM-E2165 | Computer Aided Visualization and Scientific Presentation | 3-5 | IV-V / 1 |
CHEM-E8135 | Microfluidics and BioMEMS D | 5 | III-IV / 1 |
Track 2: Biomaterials |
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CHEM-E2100 | Polymer Synthesis | 5 | I / 1 |
CHEM-E2130 | Polymer Properties | 5 | II / 1 |
CHEM-E3150 | Biophysical Chemistry D | 5 | III / 1 |
ELEC-E8729 | Biomaterials Interfaces | 5 | I-II / 1 or 2 |
Select two of the following courses: | |||
CHEM-E4210 | Molecular Thermodynamics D | 5 | II/2 |
CHEM-E8100 | Organic Structural Analysis D | 5 | I / 1 or 2 |
NBE-E4150 | DNA Nanotechnology | 5 | I-II / 2 |
CHEM-E8125 | Synthetic Biology | 5 | IV-V / 1 |
Track 3: Chemistry of life |
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CHEM-E8100 | Organic Structural Analysis D | 5 | I / 1 |
CHEM-E4170 | Advanced Organic Chemistry | 5 | II / 1 |
CHEM-E8125 | Synthetic Biology | 5 | IV-V / 1 |
CHEM-E4116 | Synthesis Strategies and Design D | 5 | III / 1 |
Select two of the following courses: | |||
CHEM-E3150 | Biophysical Chemistry D | 5 | III / 1 |
ELEC-E8729 | Biomaterial Interfaces | 5 | I-II / 1 or 2 |
CHEM-E4230 | Physical Organic Chemistry D | 5 | II / 2 |
CHEM-E4210 | Molecular Thermodynamics D | 5 | II / 2 |
* If the student has taken this course during their bachelor's degree, the student should take an additional course from the selected track.
Code: SCI3060
Scope: 60 credits
Abbreviation: CS
Professor in charge: Professor Jari Saramäki
Intended learning outcomes
After completing the studies in this major the student understands complex systems from the human brain to a diversity of biological and social systems. Further, students will be able to apply computational and theoretical tools specific to the field of complex systems to analyze and solve problems. Upon completion, the students have the necessary skills for interdisciplinary scientific careers, or, e.g. for data scientist positions in the industry.
Code | Course name | ECTS | Period/Year |
---|---|---|---|
JOIN-E3100 | Life Science Technologies Project Course A | 2 | I/1 |
JOIN-E3200 | Life Science Technologies Project Course B | 8 | III-V/1 |
Select at least 25 ECTS from the courses below. |
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CS-E5740 | Complex Networks (recommended) | 5 | I-II/1 |
CS-E5775 | Complex Systems (recommended) | 5 | I/1 |
CS-E5795 | Computational Methods in Stochastics | 5 | I-II/1 |
MS-C2111 | Stochastic Processes | 5 | II/1 |
CS-E5745 | Mathematical Methods for Network Science | 5 | III/1 |
MS-E2112 | Multivariate Statistical Analysis | 5 | III-IV/1 |
CS-E5755 | Nonlinear Dynamics and Chaos | 5 | III-IV/1 |
CS-E5700 | Hands-on Network Analysis | 5 | IV-V/1 |
Select courses from one or several themes for 60 ECTS in total. |
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Theme 1: Systems and applications |
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CS-E5885 | Modeling Biological Networks | 5 | II/1 |
MS-E1603* | Random Graphs and Network Statistics* | 5 | V/1 |
CS-C4100 | Digital Health and Human Behaviour | 5 | II/1 or 2 |
CS-E4730 | Computational Social Science | 5 | IV-V/1 |
Theme 2: Theory |
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MS-E1603* | Random Graphs and Network Statistics* | 5 | V/1 |
MS-E1050 | Graph Theory | 5 | I/1 or 2 |
CS-E4565 | Combinatorics of Computation | 5 | V/1 |
MS-E1052* | Combinatorial Network Analysis | 5 | II/2 |
Theme 3: Data science |
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CS-E4840 | Information Visualization | 5 | IV/1 |
CS-E4715 | Supervised Machine Learning | 5 | I-II/2 |
CS-E5710 | Bayesian Data Analysis | 5 | I-II/1 |
CS-E4650 | Methods of Data Mining | 5 | I-II/1 or 2 |
CS-E4890 | Deep Learning | 5 | III-IV/1 |
CS-E4640 | Big Data Platforms | 5 | III-IV/1 |
Theme 4: Special courses |
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CS-E5780 ** | Special Assignment in Complex Systems** | 5-10 | |
CS-E5770 | Special Course in Complex Systems | 1-10 | I-II/1 or 2, or III-summer/1 |
Theme 5: Courses from other Life Science Technologies majorsPick any courses from other Life Science Technologies majors. |
*Not lectured in 2024-2025
**On request
Code: SCI3061
Scope: 65 credits
Abbreviation: NEURO
Professor in charge: Lauri Parkkonen
Content description
This major gives the students a strong background for understanding structure and function of the human brain, human cognition, as well as theoretical and practical knowledge of brain research methods and other neurotechnologies. After completing their studies, the students have an excellent background for a career in science and for applying their expertise in more applied fields such as medical technology, health and wellbeing, and game industry.
Intended learning outcomes
After graduating from the Human Neuroscience and Technology major, the students
- will have solid foundational knowledge on the human brain, both on its structure and function
- will be able to describe the core components of human cognition
- will be able to perform brain-imaging experiments with selected methods
- will be able to analyze various brain measurements
- will be able to apply neuroscientific knowledge and methods in neurotechnology
- will possess skills to work with complex, multidimensional and noisy data and to extract relevant information from them
Code | Course name | ECTS | Period/Year |
---|---|---|---|
JOIN-E3100 | Life Science Technologies Project Course A | 2 | I/1 |
JOIN-E3200 | Life Science Technologies Project Course B | 8 | III-V/1 |
Select courses from the themes according to the instructions. |
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Theme 1: Neuroscience and imaging (30 credits) |
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NBE-E4210 | Structure and Operation of the Human Brain | 5 | I-II/1 |
NBE-E4225 | Cognitive Neuroscience | 5 | III/1 |
NBE-E4240 | Advanced Course on Human Neuroscience | 5 | IV-V/1 |
NBE-E4045 | Functional Brain Imaging | 5 | I-II/2 |
NBE-E4600* | Special Assignment* | 10 | I-V, summer/1 or 2 |
Theme 2: Analysis and modeling (15-20 ECTS)Select 15-20 ECTS. |
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NBE-E4070 | Basics of Biomedical Data Analysis | 5 | I-II/1 |
NBE-E4260 | Genesis and Analysis of Brain Signals | 5 | III-IV/1 |
NBE-E4060 | Bioelectromagnetism: Fundamentals, Modelling and Application | 5 | I-II/1 or 2 |
CS-E5710 | Bayesian Data Analysis | 5 | I-II/2 |
CS-E4715 | Supervised Machine Learning | 5 | I-II/1 or 2 |
CS-E5740 | Complex Networks | 5 | I-II/1 or 2 |
Theme 3: Supporting courses (5-10 ECTS)Select as many courses as needed to fulfil the 65 ECTS requirement. Select primarily from the ones below or from the courses listed in Analysis and modelling above. Other relevant courses from other Life Science Technologies majors are possible with an agreement of the responsible professor of the major. |
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NBE-E4120 | Cellular Electrophysiology | 5 | I-II (even years) |
NBE-E4130 | Information Processing in Neural Circuits | 5 | III-V (odd years) |
NBE-E4010 | Medical Image Analysis | 5 | I-II/1 or 2 |
NBE-E4020 | Medical Imaging | 5 | III-IV (even years) |
NBE-E4300 | Medical Device Innovation | 5 | III-IV/1 |
NBE-E4305 | Biodesign–innovating medical technologies in multidisciplinary teams | 5 | V/1 |
NBE-E4250 | Mapping, Decoding and Modeling the Human Brain | 5 | III (odd years) |
NEU-104 ** | Integrative neurobiology** | 5 | |
NEU-521 ** | Basic mechanisms of nervous system diseases** | 1-5 |
* The Special Assigment should be done before starting writing the master's thesis.
** The course is organised by University of Helsinki. Course information is available on Sisu system of University of Helsinki. Please note that to take the course, you need to apply for non-degree study right with this application form. When you have completed the course, you need to apply for credit transfer (inclusion). Instructions on applying for credits transfer are available at Sisu instructions.
Master's Thesis 30 ECTS
Students are required to write a master's thesis, which is an individual research project with a workload of 30 credits. The topic of the thesis is usually related to the student’s major, or in some special cases to a minor. The thesis work must have one supervisor and may have one or two advisors. The supervisor is a professor at Aalto University who ensures that the thesis meets all aims and requirements set by the schools responsible for the programme. The advisor is usually from an organization for which the thesis is written. The thesis advisor shall hold at least a master’s degree. The advisor is an expert in the field of the thesis, who can give advice on content and writing of a thesis. The duties of the advisor are agreed on by the student, supervisor, and advisor.
Master’s thesis work also includes a maturity essay, and a seminar presentation or an equivalent presentation.
The master’s thesis is a public document and cannot be concealed. The approved thesis shall be kept available in electronic form at the university.
Elective studies 25-30 ECTS
Students choose 25–30 credits of elective studies depending on the extent of the major. As elective studies, students can
- select individual courses from their major or other majors of the programme
- select individual courses from other programmes at Aalto University
- select language and communication courses
- select a minor
- select individual courses form other Finnish Universities
- participate in an international student exchange programme
- include 1-10 ECTS of work experience completed in Finland or abroad.
- students of Bioinformatics and Digital Health, Biomedical Engineering, Biosensing and Bioelectronics, Complex Systems, and Human Neuroscience and Technology can include up to 10 credits of work experience in the degree. However, students that have completed course JOIN-A0003 Contributing in Community (3 ECTS) can include up to 7 credits of work experience in the degree.
- Students of Biosystems and Biomaterials Engineering can include up to 5 credits of work experience in the degree.
Elective studies must be university level studies that fulfill the degree requirements and, in general, studies that are offered as degree studies at the university in question. Universities also offer courses that are targeted for a larger audience. The suitability of these studies is evaluated taking into consideration the learning outcomes of the degree that the courses are planned to be included in. Elective studies may not overlap with student's other studies. For this reason, the programme may restrict the choices in elective studies.
You can find more information at the following links:
Studies at other Aalto Schools or in Finnish Universities
Practical Training (work experience)
Recommendations of majors on elective studies
Bioinformatics and Digital Health
For the elective studies to accompany the Bioinformatics and Digital Health major, it is recommended to take a minor subject or an international mobility period or an internship. The autumn period of second year is the recommended time period for elective studies.
Life Science Technologies programme minors:
- Biomedical engineering
- Biosensing and Biolectronics
- Complex systems
- Human Neuroscience and Technology
Computer, Communications, and Information Science programme minors:
- Machine Learning, Data Science and Artificial Intelligence
An international mobility period of approximately one semester is recommended. The suitable timing for mobility is Autumn period of the second study year.
University of Helsinki (www.helsinki.fi) offers courses suitable for elective studies in
- Algorithmic bioinformatics
- Molecular biosciences
- Biomedicine
Courses offered by University of Helsinki can be taken through the Flexible Study Rights (JOO) agreement. Further information on JOO studies is available on aalto.fi.
Biomedical Engineering
For the elective studies to accompany the biomedical engineering major, we recommend to take a minor subject, an international mobility period or an internship. The autumn term of second year is the recommended time for international mobility. For students interested in health technology innovation and industry, we recommend applying to HealthTech Linkage program offered by Department of Industrial Engineering and Management.
Life Science Technologies programme minors:
- Bioinformatics and Digital Health
- Biosensing and Bioelectronics
- Biosystems and Biomaterials Engineering
- Complex Systems
- Human Neuroscience and Technology
Other majors:
- Engineering Physics
- Mathematics
An international mobility period of approximately one term is recommended. The suitable timing for mobility is the autumn term of the second study year.
Biosystems and Biomaterials Engineering
For the elective studies to accompany the major, it is recommended to take a minor subject.
Life Science Technologies programme minors:
- Bioinformatics
- Biosensing and Bioelectronics
- Complex Systems
- Human Neuroscience and Technology
- Biomedical engineering.
Suitable elective courses can be found from the list of elective specialization courses and selected courses from Bioinformatics or other majors in Life Science Technologies program.
Complex Systems
In their elective studies, the students are encouraged to take courses from other majors of the LifeTech programme, according to their interests. Courses in the field of information and computer science are also recommended. Internship and exchange are also recommended in elective studies.
Human Neuroscience and Engineering
Students are encouraged to take courses from other Majors of the Life Sciences Technologies programme, depending on own interests. Those who are especially interested in neurotechnologies, can extend their knowledge profile by taking courses from Biomedical Engineering major and Biosensing and Bioelectronics major.
If you have completed your bachelor's degree in Finland (in Aalto or in another higher education institute), you have fulfilled the compulsory language requirements in the respective degree or received the exemption. You do not need to complete language studies in the master's degree.
If your language of education is Finnish or Swedish and you have completed your bachelor’s degree outside of Finland, you must
- demonstrate proficiency in national languages by writing the maturity test in your language of education (Finnish or Swedish) and complete the language proficiency tests (2 ECTS) in the other national language. Read more about the language of education here. You may also apply for an exemption of demonstrating proficiency in national languages.
- complete 3 ECTS in one foreign language (including both oral (o) and written (w) proficiency).
If you have completed your bachelor’s degree outside of Finland, you are required to complete only 3 ECTS in one foreign language (including both oral (o) and written (w) proficiency). Students, whose language of education is not Finnish or Swedish, may alternatively complete an elementary course in Finnish or in Swedish. The courses in national languages can be at any level on CEFR scale.
Language studies are included in students’ elective studies and are agreed in the personal study plan (HOPS). Language center offers the language studies.
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