For more details on the courses, please refer to the Course Catalog
| Code | Course Title | Credit | Learning Time | Division | Degree | Grade | Note | Language | Availability |
|---|---|---|---|---|---|---|---|---|---|
| BPC5006 | Biochip Design and Fabrication | 3 | 6 | Major | Master/Doctor | 1-8 | Biophysics | - | No |
| The main objective of this course is to introduce the theoretical background and the relevant fabrication methods required to design and fabricate biochips to graduate students having backgrounds in either medicine or engineering. The course will familiarize the students with the biochip design process and fabrication techniques. The principles and applications of biochips will be reviewed. Students will perform laboratory exercises in (1) designing biochips for specified applications and (2) fabrication of the designed biochips. | |||||||||
| BPC5011 | Printed Bioelectronics and Biosensors | 3 | 6 | Major | Master/Doctor | 1-8 | Biophysics | English | Yes |
| This course aims to introduce the basic principles and theories of fluidal and colloidal phenomena for applications in printed bioelectronics and biosensors. The course highlights various fabrication processes apart from conventional Si electronic device fabrication in which vacuum deposition and photolithography dominate. Upon taking this course, the student will garner fundamentals in the mechanism and function of printed biochips and sensors, and will ultimately be able to design novel biochips and biosensors. | |||||||||
| BPC5012 | Large-scale Additive Manufacturing Process in Biochip Production | 3 | 6 | Major | Master/Doctor | 1-8 | Biophysics | - | No |
| This course aims to introduce the basic principles of large-scale additive manufacturing process as an environmentally benign and inexpensive approach towards biochip production. Upon taking this course, students will be knowledgeable of the production limits delineated by advanced additive manufacturing and apply these parameters toward designing a mass-producible biochip. | |||||||||
| BPC5013 | 3D printed chip design and fabrication | 3 | 6 | Major | Master/Doctor | 1-8 | Biophysics | - | No |
| The main objective of the course is to introduce 3D bioprinting used in lab-on-chips to graduate students having a background in engineering. The course should familiarize the students with the techniques used in 3D bioprinting and show them how 3D printing technology pervades throughout various regenerative medicine. | |||||||||
| BPC5014 | IQB Colloquim1 | 3 | 6 | Major | Master/Doctor | 1-8 | Biophysics | English | Yes |
| The main objective of the course is for IQB students to learn research topics in multiple areas, widen their insights, and consequently elevate their research. This course is composed of weekly seminars provided by speakers from SKKU and others with introductory to and recent publications in their multidisciplinary areas. | |||||||||
| BPC5015 | IQB Colloquim2 | 3 | 6 | Major | Master/Doctor | 1-8 | Biophysics | English | Yes |
| The main objective of the course is for IQB students to learn research topics in multiple areas, widen their insights, and consequently elevate their research. This course is composed of weekly seminars provided by speakers from SKKU and others with introductory to and recent publications in their multidisciplinary areas. | |||||||||
| BPC5016 | Molecular Biophysical Methods | 3 | 6 | Major | Master/Doctor | 1-8 | Biophysics | - | No |
| This course provides students with majors in physics, chemistry, engineering, and medicine, and graduate school students to understand biophysical knowledge of biomolecules and cells in order to learn relevant experimental methods in terms of handling biological samples. Students will learn how to classify and quantitatively analyze biomolecules and cells through specific, precise, and effective labeling, extraction, seperation, and detection techniques for biomolecules and cells in vitro. | |||||||||
| BPC5018 | Advanced Research for Quantum Biophysics1 | 3 | 6 | Major | Master/Doctor | 1-8 | Biophysics | - | No |
| this class has been designed to enhance the knowledge and research power in the field of quantum biophysics so that students can provide competitiveness in their research for their thesis and lead the research in the undeveloped fields. | |||||||||
| BPC5019 | Advanced Research for Quantum Biophysics 2 | 3 | 6 | Major | Master/Doctor | 1-8 | Biophysics | - | No |
| This class has been designed to enhance the knowledge and research power in the field of quantum biophysics so that students can provide competitiveness in their research for their thesis and lead the research in the undeveloped fields. | |||||||||
| BPC5021 | Quantum Biophysics and Application | 3 | 6 | Major | Master/Doctor | 1-8 | Biophysics | - | No |
| This course aims to understand living cellular system by analyzing various phenomena of complex living things using quantum physics theory and methods. To understand and comprehend the quantum mechanical phenomena for the electron transport in proteins and nucleic acids in the nanoscale biological world, and how quantum mechanical phenomena affect the intracellular energy metabolism and signal transduction pathways in the cells. In addition, students will learn about quantum biological research methods by review the results of research papers in the field of integration of quantum physics and biology. | |||||||||
| BPC5023 | Quantum Life Science and Its Biomedical Applications | 3 | 6 | Major | Master/Doctor | 1-8 | Biophysics | English | Yes |
| This course aims to learn the basic principles of quantum biophysics, which are essential for understanding quantum life science phenomena. This course is mainly composed of 3 parts, and aims to learn in detail 1) the basics of quantum physics, 2) the basics of quantum optics, and 3) the application of quantum biophysics. After this course, students will be able to understand and explain underlying quantum mechanical principles in photosynthesis, enzyme, magnetoreceptor, DNA mutation and human sensory system. | |||||||||
| BPC5024 | Quantum computing and brain | 3 | 6 | Major | Master/Doctor | 1-8 | Biophysics | - | No |
| Free discussion based Lecture - Research papers based lecture - Case research proposal - Practice of mock -up proposal presentation of own toptics | |||||||||
| BSE5001 | Introduction to Cognitive AI | 3 | 6 | Major | Master/Doctor | Brain Science and Engineering | - | No | |
| This course will provide an advanced introduction to the emerging field at the intersection of cognitive neuroscience and artificial intelligence, focusing on how insights from human cognition can inform next-generation AI systems, and how AI can in turn advance our understanding of the mind. During the course, we will cover key topics such as reinforcement learning and decision-making, probabilistic reasoning, attention and working memory, abstraction, and metacognition. Students will critically examine computational models inspired by human cognition and deep learning architectures, while discussing their neuroscientific and psychological foundations. Special emphasis will be placed on current debates around interpretability, generalisation, and the scaling limits in AI. The course will also address applications to neuroscience, psychiatry, and human–machine interaction. Through reading, discussion, and group-led presentations, students will gain an in-depth understanding and knowledge to evaluate and implement cognitive models of intelligence, assess their biological relevance for the brain, and consider implications for building robust and human-aligned AI systems. | |||||||||
| BSE5002 | Causal approaches in human neuroscience | 3 | 6 | Major | Master/Doctor | Brain Science and Engineering | English | Yes | |
| This course will provide a comprehensive overview of experimental approaches that move beyond correlation to establish causal links between brain activity and behaviour. The course will provide an advanced introduction to contemporary methods including noninvasive brain stimulation (TMS, tDCS, tACS), real-time fMRI, and machine learning-based neurofeedback, alongside advanced computational modelling. It will emphasise the strengths and limitations of each technique, the logic of experimental design, and the ethical considerations of interventions on the human brain. Students will learn how causal approaches are used to test mechanistic theories of perception, decision-making, learning, and emotion, as well as their applications in clinical research and translational neurotechnology. Students will engage with primary research articles, participate in methodological debates, and design their own causal experiment proposal. By the end of the course, participants will be equipped to critically assess causal claims in neuroscience and to integrate these methods into their own research programs. | |||||||||
| BSE5003 | The Neuroscience of Metacognition | 3 | 6 | Major | Master/Doctor | Brain Science and Engineering | English | Yes | |
| This class explores recent and ongoing cutting-edge research on the neuroscience of metacognition—the capacity to monitor and regulate one’s own cognitive processes. The course offers an advanced introduction to: i) how metacognition emerges from distributed brain networks and how it might shape learning and decision-making. The course integrates evidence from neuroimaging, computational modelling, lesion studies, and neurostimulation, with a focus on domains such as memory, perception, and value-based choice. ii) special attention will be given to current debates, including whether metacognition is domain-general or domain-specific, how metacognitive dysfunction might contribute to psychiatric and neurological disorders, and whether we can develop artificial intelligence with metacognitive functions. Students will critically evaluate recent empirical and theoretical work, engage with the literature, and develop skills in synthesising findings across methods and disciplines. Through presentations and discussions, participants will gain a deep understanding of state-of-the-art approaches to metacognition and their implications for cognitive neuroscience, psychiatry, and artificial intelligence. | |||||||||