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13.01.2020, Wissenschaftliches Personal PhD position at the Chair of Algorithms and Complexity. Candidate shall work on approximation algorithms for scheduling problems in parallel and distributed
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theoretical research, algorithm design, and the development of software tools that demonstrate the applicability of the new methods. Research environment The positions are hosted by the Department
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for long-term monitoring to confirm successful restoration5. This exciting and timely PhD will develop and deploy a range of low-cost and open-source sensors to measure the biophysical properties necessary
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objects, by embedding them into a 2 or 3-dimensional space through a representation learning algorithm, has been widely used for data exploratory analysis. It is particularly popular in areas such as
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expertise in autonomous marine systems. The research focus will be on development, implementation and verification of novel algorithms for motion planning and control of autonomous underwater vehicles. You
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structure of the resulting supracrystals plays a key role in determining their macroscopic properties, and hence their suitability for technological application as e.g. catalysts, sensors, or photonic
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Forschungsinstitut für Nutztierbiologie (FBN) | Dummerstorf, Mecklenburg Vorpommern | Germany | 2 days ago
, animal science, biology or related biosciences Basic knowledge of animal behavior, animal physiology, animal nutrition and organic farming High motivation to work with cattle and sensor technologies (GPS
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Chemistry, Engineering Chemistry, Biochemistry, Biotechnology, Nanotechnology, or related fields. - Proven experience in one or more of the following areas: o (Bio)chemical sensors o Electrochemistry o
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, you will contribute to developing closed-loop algorithms for regulating brain dynamics with clinical applications in epilepsy and psychiatric disorders. Number Of Awards: 1 Start Date: September/October
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" (Supervisor: Prof Timothy O'Leary) uses principles from systems neuroscience to develop reliable, low-power spiking neural networks and learning algorithms for implementation in a new generation of neuromorphic