Suchergebnis: Katalogdaten im Frühjahrssemester 2021

Doktorat Departement Gesundheitswissenschaften und Technologie Information
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Gesundheitswissenschaften und Technologie
» Auswahl aus sämtlichen Lehrveranstaltungen der ETH Zürich
327-2225-00LMaP Distinguished Lecture Series on Soft Robotics
This course is primarily designed for MSc and doctoral students. Guests are welcome.
W1 KP2SR. Katzschmann, L. Schefer
KurzbeschreibungThis course is an interdisciplinary colloquium on Soft Robotics involving different internationally renowned speakers from academia and industry giving lectures about their cutting-edge research, which highlights the state-of-the-art and frontiers in the Soft Robotics field.
LernzielParticipants become acquainted with the state-of-the-art and frontiers in Soft Robotics, which is a topic of global and future relevance from the field of materials and process engineering. The self-study of relevant literature and active participation in discussions following presentations by internationally renowned speakers stimulate critical thinking and allow participants to deliberately discuss challenges and opportunities with leading academics and industrial experts and to exchange ideas within an interdisciplinary community.
InhaltThis course is a colloquium involving a selected mix of internationally renowned speaker from academia and industry who present their cutting-edge research in the field of Soft Robotics. The self-study of relevant pre-read literature provided in advance to each lecture serves as a basis for active participation in the critical discussions following each presentation.
SkriptSelected scientific pre-read literature (max. three articles per lecture) relevant for and discussed during the lectures is posted in advance on the course web page.
Voraussetzungen / BesonderesParticipants should have a solid background in materials science and/or engineering.
376-1792-00LIntroductory Course in Neuroscience II (University of Zurich)
Der Kurs muss direkt an der UZH belegt werden.
UZH Modulkürzel: SPV0Y020

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W2 KP2VUni-Dozierende
KurzbeschreibungThis course discusses behavioral aspects in neuroscience. Modern brain imaging methods are described. Clinical issues including diseases of the nervous system are studied. Sleep research and neuroimmunology are discussed. Finally, the course deals with the basic concepts in psychiatry.
Voraussetzungen / BesonderesFür Doktorierende des Zentrums für Neurowissenschaften Zürich.
376-1986-00LBayesian Data Analysis and Models of Behavior (University of Zurich)
Der Kurs muss direkt an der UZH belegt werden.
UZH Modulkürzel: DOEC0829

Beachten Sie die Einschreibungstermine an der UZH: Link
W3 KP2SR. Polania, Uni-Dozierende
KurzbeschreibungMaking sense of the data acquired via experiments is fundamental in many fields of sciences. This course is designed for students/researchers who want to gain practical experience with data analysis based on Bayesian inference. Coursework involves practical demonstrations and discussion of solutions for data analysis problems. No advanced knowledge of statistics and probability is required.
LernzielThe overall goal of this course it that the students are able to develop both analytic and problem-solving skills that will serve to draw reasonable inferences from observations. The first objective is to make the participants familiar with the conceptual framework of Bayesian data analysis. The second goal is to introduce the ideas of modern Bayesian data analysis, including techniques such as Markov chain Monte Carlo (MCMC) techniques, alongside the introduction of programming tools that facilitate the creation of any Bayesian inference model. Throughout the course, this will involve practical demonstrations with example datasets, homework, and discussions that should convince the participants of this course that it is possible to make inference and understand the data acquired from the experiments that they usually obtain in their own research (starting from simple linear regressions all the way up to more complex models with hierarchical structures and dependencies). After working through this course, the participants should be able to build their own inference models in order to interpret meaningfully their own data.
Voraussetzungen / BesonderesThe very basics (or at least intuition) of programming in either Matlab or R
376-0304-00LColloquium in Translational Science (Spring Semester)W1 KP1KN. Cesarovic, A. Alimonti, C. Ewald, V. Falk, J. Goldhahn, K. Maniura, M. Ristow, R. M. Rossi, S. Schürle-Finke, G. Shivashankar, E. Vayena, V. Vogel, F. von Meyenn
KurzbeschreibungCurrent topics in translational medicine presented by speakers from academia and industry.
LernzielGetting insight into actual areas and problems of translational medicine.
InhaltTimely and concise presentations of postgraduate students, post-docs, senior scientists, professors, as well as external guests from both academics and industry will present topics of their interest related to translational medicine.
Voraussetzungen / BesonderesNo compulsory prerequisites, but student should have basic knowledge about biomedical research.
376-0306-00LETHeart Joint Scientific Colloquium (Spring Semester)W1 KP1KN. Cesarovic, V. Falk, weitere Dozierende
KurzbeschreibungLectures, presentations and discussions on chosen topics in biologics, (bio-) materials, devices, sensors, robotics and data science and their relevance for cardiovascular medicine.
LernzielDeeper, mutual understanding of current medical challengesand technical solutionsin cardiovascular medicine.
InhaltTimely and didacticaly stuctured presentations of postgraduate students, post-docs, senior scientists and professorson topics from Zurich Heart / ETHeart projects, followed by lectures on chosen topics of cardiovascular medicine and research given by leading international clinical scientists in the field.
Voraussetzungen / BesonderesNo compulsory prerequisites, but students should have basic knowledge about cardiovascular system, physiology and biomedical research.
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