Suchergebnis: Lehrveranstaltungen im Frühjahrssemester 2019

Computational Biology and Bioinformatics Master Information
More informations at: Link
Master-Studium (Studienreglement 2017)
Kernfächer
Please note that the list of core courses is a closed list. Other courses cannot be added to the core course category in the study plan. Also the assignments of courses to core subcategories cannot be changed.
Students need to pass at least one course in each core subcategory.
A total of 40 ECTS needs to be acquired in the core course category.
Bioinformatics
Please note that all Bioinformatics core courses are offered in the autumn semester
Biophysics
NummerTitelTypECTSUmfangDozierende
551-0307-01LMolecular and Structural Biology II: From Gene to Protein
D-BIOL students are obliged to take part I and part II as a two-semester course.
W3 KP2V
551-0307-01 VMolecular and Structural Biology II: From Gene to Protein2 Std.
Mo12:45-14:30HCI J 3 »
N. Ban, F. Allain, S. Jonas, M. Pilhofer
262-5100-00LProtein Biophysics (University of Zurich) Information
Der Kurs muss direkt an der UZH belegt werden.
UZH Modulkürzel: BCH304

Beachten Sie die Einschreibungstermine an der UZH: Link
W6 KP3V + 1U
262-5100-00 VProtein Biophysics (University of Zurich)
**Course at University of Zurich**
3 Std.Uni-Dozierende
262-5100-00 UProtein Biophysics (University of Zurich)
**Course at University of Zurich**
1 Std.Uni-Dozierende
Biosystems
NummerTitelTypECTSUmfangDozierende
636-0006-00LComputational Systems Biology: Deterministic Approaches Belegung eingeschränkt - Details anzeigen W4 KP3G
636-0006-00 GComputational Systems Biology: Deterministic Approaches Für Fachstudierende und Hörer/-innen ist eine Spezialbewilligung der Dozierenden notwendig.
Students are expected to have completed the courses Computational systems biology’ and ‘Spatio-temporal modeling in biology’ (MSc Computational biology and bioinformatics), which provide the foundational knowledge for the course.
3 Std.
Di13:15-16:00BSB E 4 »
J. Stelling, D. Iber
636-0016-00LComputational Systems Biology: Stochastic Approaches Information W4 KP3G
636-0016-00 GComputational Systems Biology: Stochastic Approaches
This lecture will be recorded.
3 Std.
Mo14:15-17:00BSA E 46 »
M. H. Khammash, A. Gupta
636-0111-00LSynthetic Biology I
Attention: This course was offered in previous semesters with the number: 636-0002-00L "Synthetic Biology I". Students that already passed course 636-0002-00L cannot receive credits for course 636-0111-00L.
W4 KP3G
636-0111-00 GSynthetic Biology I
ATTENTION: the lecture starts at exactly 08.00 am.
The lecture will be held either in Zurich or Basel and will be transmitted via videoconference to the second location.
3 Std.
Mi07:45-10:30HCI J 3 »
08:15-11:00BSA E 46 »
S. Panke, J. Stelling
Data Science
NummerTitelTypECTSUmfangDozierende
551-0364-00LFunctional Genomics
Information for UZH students:
Enrolment to this course unit only possible at ETH. No enrolment to module BIO 254 at UZH.

Please mind the ETH enrolment deadlines for UZH students: Link
W3 KP2V
551-0364-00 VFunctional Genomics
**together with University of Zurich**
2 Std.
Mo15:15-17:00ML H 41.1 »
C. von Mering, C. Beyer, B. Bodenmiller, M. Gstaiger, H. Rehrauer, R. Schlapbach, K. Shimizu, N. Zamboni, weitere Dozierende
636-0702-00LStatistical Models in Computational BiologyW6 KP2V + 1U + 2A
636-0702-00 VStatistical Models in Computational Biology
The lecture will be held either in Zurich or Basel and will be transmitted via videoconference to the second location.
2 Std.
Do12:15-14:00BSB E 4 »
12:15-14:00HG D 16.2 »
N. Beerenwinkel
636-0702-00 UStatistical Models in Computational Biology
The tutorial will be held either in Zurich or Basel and will be transmitted via videoconference to the second location.
1 Std.
Do14:15-15:00BSB E 4 »
14:15-15:00HG D 16.2 »
N. Beerenwinkel
636-0702-00 AStatistical Models in Computational Biology
Project work, no fixed presence required.
2 Std.N. Beerenwinkel
636-0019-00LData Mining II
Prerequisites: Basic understanding of mathematics, as taught in basic mathematics courses at the Bachelor`s level. Ideally, students will have attended Data Mining I before taking this class.
W6 KP3G + 2A
636-0019-00 GData Mining II
The lecture will be held each Wednesday either in Zurich or Basel and will be transmitted via videoconference to the second location.
Lecture in Basel/Zürich: Wednesday 14-16h, Tutorial 16-17h (BSB E4 Room "Manser" / HG D16.2)
3 Std.
Mi14:15-17:00BSB E 4 »
14:15-17:00HG D 16.2 »
K. M. Borgwardt
636-0019-00 AData Mining II
Project Work (compulsory continuous performance assessment), no fixed presence required.
2 Std.K. M. Borgwardt
262-6190-00LMachine LearningW8 KP4G
262-6190-00 GMachine Learning (University of Basel)
**Course at University of Basel**
Link
4 Std.externe Veranstalter
Seminar
Compulsory seminar.
NummerTitelTypECTSUmfangDozierende
636-0704-00LComputational Biology and Bioinformatics SeminarO2 KP2S
636-0704-00 SComputational Biology and Bioinformatics Seminar2 Std.
Do15:15-17:00CHN D 48 »
J. Stelling, M. Claassen, D. Iber, T. Stadler
Vertiefungsfächer
A total of 30 ECTS needs to be acquired in the Advanced Courses category. Thereof 18 ECTS in the Theory and 12 ECTS in the Biology category.
Theorie
At least 18 ECTS need to be acquired in this category.
NummerTitelTypECTSUmfangDozierende
252-0063-00LData Modelling and Databases Information W7 KP4V + 2U
252-0063-00 VData Modelling and Databases4 Std.
Mi13:15-15:00ML D 28 »
Fr08:15-10:00HG F 3 »
G. Alonso, C. Zhang
252-0063-00 UData Modelling and Databases2 Std.
Do15:15-17:00CAB G 11 »
Fr13:15-15:00CHN C 14 »
G. Alonso, C. Zhang
401-0674-00LNumerical Methods for Partial Differential Equations
Nicht für Studierende BSc/MSc Mathematik
W8 KP2G + 2P + 4A
401-0674-00 GNumerical Methods for Partial Differential Equations
This course is designed in a flipped classroom format.
Attendance at the question and answer session ("Zentralübung") on Mondays 15-17 is expected. In addition, a Study Center is offered Mon 17-21 in HG E 41.
2 Std.
Mo15:15-17:00HG F 1 »
R. Hiptmair
401-0674-00 PNumerical Methods for Partial Differential Equations
Homework C++ coding projects for the course "Numerical Methods for Partial Differential Equations"
2 Std.R. Hiptmair
401-0674-00 ANumerical Methods for Partial Differential Equations
Video guided self-study or group-study for the course "Numerical Methods for Partial Differential Equations"
4 Std.R. Hiptmair
401-3052-05LGraph Theory Information W5 KP2V + 1U
401-3052-05 VGraph Theory28s Std.
Mi/110:15-12:00HG E 1.1 »
Do/110:15-12:00HG E 1.1 »
B. Sudakov
401-3052-05 UGraph Theory7s Std.
Do/115:15-16:00CAB G 52 »
15:15-16:00CAB G 56 »
15:15-16:00HG D 5.3 »
15:15-16:00HG E 21 »
B. Sudakov
227-1034-00LComputational Vision (University of Zurich) Information
No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH.
UZH Module Code: INI402

Mind the enrolment deadlines at UZH:
Link
W6 KP2V + 1U
227-1034-00 VComputational Vision (University of Zurich)
**Course at University of Zurich**
2 Std.
Do17:15-19:00Y35 F 32 »
D. Kiper
227-1034-00 UComputational Vision (University of Zurich)
**Course at University of Zurich**
Exercise dates by arrangement.
1 Std.n. V.D. Kiper
252-0220-00LIntroduction to Machine Learning Information Belegung eingeschränkt - Details anzeigen
Previously called Learning and Intelligent Systems.
W8 KP4V + 2U + 1A
252-0220-00 VIntroduction to Machine Learning
Die Vorlesung findet jeweils (Di 13-15 und Mi 13-15) im HG E 7 mit Videoübertragung im HG E 5 und HG E 3 statt.
4 Std.
Di13:15-15:00HG E 3 »
13:15-15:00HG E 5 »
13:15-15:00HG E 7 »
Mi13:15-15:00HG E 3 »
13:15-15:00HG E 5 »
13:15-15:00HG E 7 »
A. Krause
252-0220-00 UIntroduction to Machine Learning2 Std.
Mo15:15-17:00HG D 1.2 »
Di15:15-17:00HG D 1.2 »
Mi15:15-17:00CAB G 11 »
Fr13:15-15:00ML D 28 »
A. Krause
252-0220-00 AIntroduction to Machine Learning
No presence required.
1 Std.A. Krause
227-0558-00LPrinciples of Distributed Computing Information W6 KP2V + 2U + 1A
227-0558-00 VPrinciples of Distributed Computing2 Std.
Mi08:15-10:00CAB G 11 »
R. Wattenhofer, M. Ghaffari
227-0558-00 UPrinciples of Distributed Computing
In Gruppen
2 Std.
Mi10:15-12:00CAB G 56 »
13:15-15:00LFW C 11 »
R. Wattenhofer, M. Ghaffari
227-0558-00 APrinciples of Distributed Computing
No presence required.
Creative task outside the regular weekly exercises.
1 Std.R. Wattenhofer, M. Ghaffari
401-3632-00LComputational StatisticsW8 KP3V + 1U
401-3632-00 VComputational Statistics
On 18 April 2019 the course takes place in HG E 3.
3 Std.
Do13:15-15:00HG F 3 »
Fr09:15-10:00HG G 3 »
18.04.13:15-15:00HG E 3 »
M. H. Maathuis
401-3632-00 UComputational Statistics
A "Präsenzstunde" directly following the exercises will be offered Friday 11-12 in HG F 3.
1 Std.
Fr10:15-11:00HG F 3 »
M. H. Maathuis
101-0178-01LUncertainty Quantification in Engineering Information W3 KP2G
101-0178-01 GUncertainty Quantification in Engineering2 Std.
Do14:45-16:30HCP E 47.2 »
B. Sudret, S. Marelli
263-2300-00LHow To Write Fast Numerical Code Information Belegung eingeschränkt - Details anzeigen
Number of participants limited to 84.

Prerequisite: Master student, solid C programming skills.

Takes place the last time in this form.
W6 KP3V + 2U
263-2300-00 VHow To Write Fast Numerical Code3 Std.
Mo10:15-12:00HG D 3.2 »
Do09:15-10:00CAB G 51 »
M. Püschel
263-2300-00 UHow To Write Fast Numerical Code2 Std.
Mi13:15-15:00HG D 3.2 »
M. Püschel
252-0526-00LStatistical Learning Theory Information W7 KP3V + 2U + 1A
252-0526-00 VStatistical Learning Theory3 Std.
Mo14:15-16:00HG E 5 »
Di09:15-10:00HG E 5 »
J. M. Buhmann
252-0526-00 UStatistical Learning Theory2 Std.
Mo16:15-18:00HG E 5 »
J. M. Buhmann
252-0526-00 AStatistical Learning Theory1 Std.J. M. Buhmann
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