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Programme Description

NeuroData, the innovative MSc in Brain and Data Science, is designed for students with diverse academic backgrounds. It equips them to meet the increasing demand in both scientific and societal spheres for the integration of advanced computational methods in solving complex neuroscience questions.

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Each partner university within the consortium has a different role during the NeuroData program.

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At Bar-Ilan University (BIU) in Israel, all students spend their first year gaining a strong foundation in neuroscience and data science. They are personally hosted by various research groups at the Brain Center. BIU’s Multidisciplinary Brain Research Center, with its 20-year history of teaching a unique Brain Sciences curriculum, launched the MSc in Brain and Data Science in 2020 to meet the demand for neuroscience and data science specialists.

 

Since its launch, this program has been highly successful and attracts many outstanding students. The curriculum of this unique program 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, culminating in the Summer School at the University of Zagreb.

 

First-Year Courses at Bar-Ilan University.

Mandatory

Machine learning and neural networks for neuroscience

Signal and Data analysis in Neuroscience

Data Science and Advanced Python concepts workshop

Data Science Applications in Neuroscience

 

Biological Module (pick one)

Introduction to cellular and systems neurophysiology

Advanced topics in system Neurophysiology

Synaptic Neurochemistry

 

Cognitive module (pick one)

Brain Imaging of Language Functions

Brain and Cognition Research in the 21 Century

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.

Summer School Program
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.

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Second year courses at IST

A student should pick 3-4 courses from the following:

Biomedical imaging  

Instrumentation and acquisition of Biosignals  

Machine Learning in Bioengineering  

Neuroimaging  

Image Processing and Vision 

Machine Learning  

Mathematical Models in Biomedicine  

Neuromodulation  

Principles of human-machine interfaces 

Biosignals and biomedical image processing 

Advance imaging techniques  

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 

Data Analysis and Integration 

Statistical Methods in Data Mining 

Information Visualization 

 

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.

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Second year courses at UniPD

Optional course units (student should choose 1 of the following course units):

Human electrophysiology

Cognitive neuroscience of action

Neuropsychological assessment and rehabilitation

Optional course units (student should choose 1 of the following course units)

Clinical neuropsychology

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 trends in neuroscience

New technologies and human behaviour

Animal models in neurobiology

 

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.

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Second year courses at VUA

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Mandatory courses: 

Neurophilosophy and Ethics 

Career and Academic Skills Portfolio 

Thesis (Internship II) 

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Elective courses (4 from the list): 

A combination of 2 Electives should be selected within the same track in period 1 (P1) and period 2 (P2) 

Track Fundamental Neurosciences 

Cellular Models for Brain Disorders P1 

Live Cell Imaging P1 

Neuron-Glia Interaction P1 

Developmental Neurobiology of the Vertebrate Brain P2 

Methods in Behavioral Neurosciences P2 

Neuronal Networks In Vivo P2 

System Neuroscience P2 

Track Clinical Neurosciences 

Neuro- and Psychopharmacology P2 

Rhythms of the Brain P2 

Experimental and Clinical Neuroendocrinology P2 

 

TOTAL (4 Electives, CASP, Neurophil&Ethics, thesis) 

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.

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Second year courses at JYU

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Select 20 ECTS from these courses

Basics of signal processing

Deep learning for cognitive computing

Deep learning for cognitive computing for developers

Collective Intelligence and agent technology

SOA and cloud computing

Communication Systems and Services

Anatomy and physiology of the central and autonomic nervous system

Experimental methods in neuroscience

Basics of brain imaging

Neuroscience practicum

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

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