Learning outcomes

Knowledge

k1. To understand the fundamentals of neuroscience and to know the neuroanatomy at the mesoscopic and macroscopic level and the physiology of the central and peripheral nervous system, as well as neuronal function and plasticity.

k2. To know the theoretical and practical aspects of advanced artificial intelligence techniques that can be used to solve multidisciplinary problems in neurotechnology.

k3. To understand the physical foundations of neurophysiological signals and state-of-the-art techniques in advanced neuroimaging.

k4. To understand the advanced concepts and techniques of electronics, biomedical instrumentation and biomaterials in Neuroengineering.

k5. To understand the main advanced concepts of neurosensory and motor prostheses, including the types of prostheses available and the basic principles of their operation.

k6. To know the methods of neuronal stimulation and neuromodulation, and to understand the main advanced concepts of brain-computer and brain-brain interfaces, and their relationships with neurosensory and motor prostheses.

Skills

s1. To apply the appropriate neurotechnology techniques (neurodevices, neuroprostheses, neurosignal processing, artificial intelligence) to mixed technological and clinical problems and to understand the challenges and opportunities associated with their application in this field.

s2. To acquire, process, analyse and model data on the activity of the nervous system and to interpret the results, implementing algorithms with the use of appropriate programming languages, freely distributed software and specialized artificial intelligence platforms.

s3. To select and apply advanced techniques in the processing of neuroelectrophysiological signals and brain images for the design, implementation and evaluation of brain-machine interfaces, and neurorehabilitation devices that allow diagnosing and treating neurological and neuropsychiatric diseases.

s4. To communicate work and conclusions to peers or to general audiences in a reasoned, clear and unambiguous manner, to prepare articles or technical reports, and to transmit in a clear way the results from scientific and technological advances or the most advanced innovation to specialized and non-specialized audiences.

s5. To use information and communication technologies to search for information and bibliographic data, and to acquire new knowledge for lifelong learning and self-employment.

Competences

c1. To apply leadership and collaborative work techniques in multidisciplinary teams, as well as to assume the responsibility of guiding and carrying out innovative work in the field of neurotechnology.

c2. To analyse and evaluate ethical and social problems related to neurotechnologies, applying the main advanced concepts and principles of neuroethics as well as deontological codes, legal regulations, guidelines and relevant professional standards to analyse situations related to ethical aspects of the field of neurotechnology.

c3. To conceive, develop and validate new neurodevices and neuroprostheses that can increase people’s quality of life, and carry out, in academic and professional contexts, innovations or technological advances that can advance the state-of-the-art in areas related to neurotechnology.

c4. To solve problems on neurodevices, neurosignals and artificial intelligence, integrating knowledge in new or poorly defined aspects of them in multidisciplinary environments.

c5. To apply methodologies, procedures, tools and state-of-the-art standards for the creation of new technological components, and to build new hypotheses and models, evaluate them and apply them to problem solving in the area of neurotechnology.

c6. To carry out, present and defend before a specifically constituted public committee of an original project of a professional, research or academic nature in the field of neurotechnology, in which the competences acquired in the studies are synthesized and integrated.

c7. To Integrate autonomously into a work environment, applying the knowledge, skills and competencies acquired in the studies, with quality and with ethical and professional responsibilities.

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Academic year calendar and schedule

Course Schedule MASTER IN SCIENCE IN NEUROTECHNOLOGY Download Relevant dates Monday 2nd September: Start of complementary training classes Thursday 12th September, 16:00h, Classroom TBD: Welcome Day Monday 16th September, 9:00h: Start of classes Monday 30th September, 17:00h, Classroom TBD: Master’s Inaugural session; keynote lecture by guest lecturer Álvaro Pascual Leone

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Professors and Learning centers

The MUNEUROTEC Master takes advantage of the heterogeneous research force of the UPM, with the participation of specialists from different schools. The teaching center responsible for the program is the Faculty of Telecommunication Engineering. The Faculty of Computer Engineering and the Faculty of Civil Engineering have participated in the creation

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Admission Criteria

The Master’s Degree in Neurotechnology at the UPM is aimed at graduates in biomedical engineering, which will be the recommended entry profile. In addition, graduates in other branches of engineering, such as telecommunication engineering, industrial and automatic engineering, data engineering, or computer engineering, which will constitute the additional entry profile,

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