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<div><font face="Calibri,sans-serif">The Max Planck ETH Center for Learning Systems is a joint research center of ETH Zurich and the Max Planck Society. The Center’s mission is to pursue research in the design and analysis of learning systems, synthetic or
natural. This initiative brings together more than 30 professors and senior researchers in the fields of machine learning, perception, robotics on large and small scales, as well as neuroscience. We offer</font></div>
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<div><font face="Calibri,sans-serif"><b>PhD Fellowships at the Max Planck ETH Center for Learning Systems</b></font></div>
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<div><font face="Calibri,sans-serif">The Center offers a unique fellowship program, where PhD students are co-supervised by one advisor from ETH Zurich and one from the MPI for Intelligent Systems in Tübingen and Stuttgart. PhD students are expected to take
advantage of the opportunities offered by both organizations and to actively seek cross-group collaborations. The Center also offers a wide range of activities like retreats, workshops, and summer schools, as well as the possibility to engage in organizing
such events. This is an exciting new program and we expect admission to be highly competitive. Each PhD fellow will have a primary location (chosen based on interests and match) and is expected to spend about one year at the other location as well. Fellowships
will be remunerated through employment contracts, subjected to the rules of the Max-Planck-Society and ETH Zurich, respectively. All PhD fellows will register as graduate students at ETH Zurich and - upon successful completion of their PhD project - be granted
a doctoral degree by ETH Zurich. Details of this process are governed by ETH regulations and committees.</font></div>
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<div><font face="Calibri,sans-serif">We encourage applications from outstanding candidates with academic backgrounds in Mathematics, Physics, Computer Science, Engineering, Materials Science, Neuroscience and related fields, and a keen interest in doing basic
research in areas like: Machine Learning and Empirical Inference of Complex Systems, Machine Intelligence, including Machine Vision and Natural Language Understanding, Perception-Action-Cycle for Autonomous Systems, Robust Model-Based Control for Intelligent
Behavior, Robust Perception in Complex Environments, Design, Fabrication, and Control of Synthetic, Bio-Inspired, and Bio-Hybrid Micro/Nanoscale Robotic Systems, Data-Driven Computational Biology, or Neurotechnology and Emergent Intelligence in Nervous Systems.
We seek to increase the number of women in areas where they are underrepresented and therefore explicitly encourage women to apply. Furthermore, we are committed to increasing the number of individuals with disabilities in its workforce and therefore encourage
applications from such qualified individuals.</font></div>
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<div><font face="Calibri,sans-serif">For further information please contact: Dr. Magdalena Seebauer at <a href="mailto:magdalena.seebauer@inf.ethz.ch">magdalena.seebauer@inf.ethz.ch</a> (no application documents) </font><font face="Calibri,sans-serif"> or visit
our website <a href="http://learning-systems.org/">http://learning-systems.org</a> </font></div>
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<div><font face="Calibri,sans-serif">We are looking forward to receiving your online application consisting of a complete CV (incl. a list of publications, talks and awards), a short mission statement (max. 1-2 pages) outlining the research interests of the
candidate, and scanned transcripts of certificates (bachelor’s degree, master’s degree, other degrees). Please arrange for 2-3 reference letters to be sent directly per email to Dr. Magdalena Seebauer. Please send your application to: ETH Zurich, Human Resources,
Mrs. Nadja Lang, CH-8092 Zurich. The deadline for applications is <b>November 15, 2016</b>. </font></div>
<div><font face="Calibri,sans-serif">The selection interviews will take place on January 19 and January 20, 2017 at the Max Planck Campus in Tübingen, Germany.</font></div>
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<div><a href="https://apply.refline.ch/845721/4942/pub/1/index.html">Apply now</a></div>
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Max Planck ETH Center for Learning Systems<br>
Dr. Magdalena Seebauer</div>
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Scientific Coordination<br>
CAB F 42.1<br>
Universitätsstrasse 6<br>
8092 Zurich<br>
Switzerland</div>
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