Erasmus Mundus Joint Master Degree Programme in Brain and Data Science
Programme Description
NeuroData, the new MSc in Brain and Data Science, accepts students with multidisciplinary backgrounds and trains students to respond to the growing need of both science and society to integrate the most suitable computational methods to solve increasingly complex questions in neuroscience.
Each partner university within the consortium has a different role to play during the NeuroData programme.
All students spend the first year at Bar-Ilan University (BIU) in Israel gaining a solid basis in neuroscience and neuroscience-orientated data science. During the first year, students will be personally hosted by the Brain Center's various research groups. BIU’s Multidisciplinary Brain Research Center has been teaching a one-of-a-kind-in-Israel, multidisciplinary Brain Sciences curriculum for nearly 20 years. In 2020, the Center launched a new MSc in Brain and Data Science to address the need for neuroscience and data science specialists.
Since this programme was launched, it has been highly successful and is attracting many outstanding students. The curriculum of this unique programme consists of core courses in neuroscience and data science, which provide students from interdisciplinary backgrounds with a solid foundation in both fields.
The first-year curriculum of NeuroData: MSc in Brain and Data Science is the foundation upon which students build knowledge, and culminates in the Summer School at the University of Zagreb.
First Year Courses at Bar-Ilan Univestity.
Mandatory
Machine learning and neural networks for neuroscience
Data Science Applications in Neuroscience
Biological Module (pick one)
Introduction to cellular and systems neurophysiology
Cognitive module (pick one)
Summer School
School of Medicine and Faculty of Electrical Engineering and Computing, University of Zagreb, Croatia
All students will participate in a compulsory joint summer school at the University of Zagreb (UNIZG), which will be held during the summer between the first and second year. This programme is designed in an innovative way that combines an introduction to the theoretical principles of neuroscience and data science with hands-on learning.
This combined approach enables students to engage actively in the programme and stimulates faster and more productive adoption of the required neuroscience and data science skill-set in a motivating environment. Students will be introduced to all steps required to conduct successfully behavioural experiments in animal models using the tools they will have developed, with micro-controllers and hardware-and-software-design skills that they will adopt throughout the course.
An interdisciplinary approach and the encouragement of independent thinking in solving tasks will give students a theoretical foundation for future projects in this field. Guest lectures from leading neuroscientists and data scientists will provide an overview of the field. Mentoring sessions with industry representatives, which will take place during the summer school, will provide students with networking opportunities. A graphical abstract of the summer course is displayed below and the provisional Sylabus can be downloaded here.
Biomedical Engineering
Department of Bioengineering, Instituto Superior Técnico
University of Lisbon, Portugal
Second-year studies at the Instituto Superior Técnico (IST) focus on the biomedical and data-science engineering aspects of neuroscience as well as biomedical and data-science engineering applications for brain research and technologies. Students will be able to expand their expertise in biomedical engineering using tools to analyse and solve critical challenges in fundamental medicine as well as those faced by clinics and hospitals while applying advanced technologies to the complex problems of health systems.
The approaches involve biological and biomedical imaging, ranging from cell microscopy to ultrasound and magnetic resonance imaging as well as physiological signals such as the electroencephalogram and electrocardiogram. A particular emphasis is on studying human brain function and neuro-engineering with applications in sleep, cognition, neurofeedback, and pathologies such as epilepsy, dementia, cerebrovascular, and psychiatric diseases.
Second year courses at IST
A student should pick 3-4 courses from the following:
Instrumentation and acquisition of Biosignals
Machine Learning in Bioengineering
Mathematical Models in Biomedicine
Principles of human-machine interfaces
Biosignals and biomedical image processing
Medical and Biological Image Processing (it will not be offered next year)
Additional electives (Master in Data Science and Engineering)
Artificial Intelligence and Decision Systems
Applied Computational Intelligence
Statistical Methods in Data Mining
Project (thesis preparation)
Thesis
Cognitive Neuroscience and Clinical Neuropsychology with Data Processing
Department of General Psychology, University of Padua, Italy
Second-year studies at the University of Padua (UniPD) focus on cognitive approaches to neuroscience, which try to capitalise on the data analysis approach for improved understanding of the neurofunctional correlates of the human mind. Activities will be based on data science approaches relevant to clinical, theoretical, and cognitive neuroscience and neuropsychology.
A particular emphasis is on understanding the human brain and mental functioning, with applications in basic research and diagnosis, cognitive or psychological rehabilitation and cognitive enhancements. In short, students will become experts in both standard and pathological aspects of the functioning of the human mind.
Second year courses at UniPD
Optional course units (student should choose 1 of the following course units):
Cognitive neuroscience of action
Neuropsychological assessment and rehabilitation
Optional course units (student should choose 1 of the following course units)
Affective neuroscience and psychopathology
Optional course units (student should choose 1 of the following course units)
Advanced social psychology and social neuroscience
New concepts in developmental psychology
Optional course units (student should choose 1 of the following course units)
Neural networks and deep learning
Machine learning for brain and cognition
New technologies and human behaviour
Internship
Thesis
Systems Neuroscience and Data Processing
Faculty of Science and Vrije University Medical Center
Vrije Universiteit Amsterdam, The Netherlands
Second-year studies at Vrije Universiteit Amsterdam (VUA) focus on fundamental, behavioural, and clinical neuroscience research. At VUA, students will expand their expertise in system neuroscience. The topics covered include Anatomy and Neurosciences, Clinical Neurophysiology, Neurology, Pathology, Physics and Medical Technology, Psychiatry, and Radiology. Clinical and translational research at the VUA is organised in world-renowned research centres where many of these departments collaborate.
Examples of these interdisciplinary collaborations include the Alzheimer's Centre, the Multiple Sclerosis (MS) Centre, and the VU medical center Imaging Centre. In short, students will be working in an interdisciplinary way, integrating information from genes and proteins to synapses and from networks to complex brain function and dysfunction. When the students graduate, they will have a clear understanding of critical scientific approaches and an awareness of the ethical and social dilemmas within the neurosciences sector.
Second year courses at VUA
Mandatory courses:
Career and Academic Skills Portfolio
Elective courses (4 from the list):
Advanced Clinical Neurosciences
Methods in Behavioral Neurosciences
Gene Finding: Genome-Wide Association Studies and beyond
Thesis (Internship II)
Cognitive Neuroscience and Neuroimaging with Data Processing
Faculty of Education and Psychology
University of Jyväskylä, Finland
Second-year studies at the University of Jyväskylä (JYU) will focus on neuroimaging and data processing in developmental, neurolinguistic, and cognitive neuroscience. The curriculum provides advanced knowledge in cognitive neuroscience, neuroimaging techniques, and data science-orientated data analysis and visualisation in this field.
JYU’s pedagogical approach is based on student-centred methods and multidisciplinary phenomenon-based teaching and learning. JYU has a long history in cognitive and behavioural neuroscience research and computational and data sciences. Moreover, JYU brings an added value of solid experience and emphasis on imaging technology, instrumentation, and development.
Second year courses at JYU
Select 20 ECTS from these courses
Deep learning for cognitive computing
Deep learning for cognitive computing for developers
Collective Intelligence and agent technology
Communication Systems and Services
Anatomy and physiology of the central and autonomic nervous system
Experimental methods in neuroscience
Current issues in cognitive neuroscience
Neurobiology of learning and memory
Developmental language-related disorders
Motor control and human neuroscience
Analysis methods for Cognitive Neuroscience
Brain development
Current applications of cognitive neuroscience
Thesis