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, R) Expertise in machine learning, Bayesian statistics is beneficial Capacity for interdisciplinary teamwork and excellent communication skills Ability to communicate in English fluently
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Max Planck Institute for Evolutionary Anthropology, Leipzig | Leipzig, Sachsen | Germany | 2 days ago
simulation in nonhuman great apes and human children across different cultures. The project employs methods such as behavioural studies, touchscreen experiments and eye tracking. The successful candidate will
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highly qualified and motivated student from any nationality and hold, or expect to hold, a Master’s degree in a related subject. You have a proven track record of academic and research excellence and are
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. Bonus lectures can be picked by the students depending on their interests and project-specific requirements. Students can deepen their knowledge about selected topics (e.g. Bayesian Statistics, HMMs, AI
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imaging methodologies. In this project, novel techniques are being developed for tracking radio-labelled cells, either as cell populations or even individual cells. This is being achieved by combining whole
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from any nationality and hold, or expect to hold, a Master’s degree in a related subject. You have a proved track record of academic and research excellence and are fluent in written and spoken English
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preferred. Prior experience in genome engineering or mass spectrometry is advantageous but not required. Strong writing skills with a proven track record of successful research are essential. Excellent
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. Postdoctoral placement at a top institution/with an active research group/professor (for those interested in the academic track). Placement in a leading research NGO/think-tank/multinational company (for those
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to co-design algorithms and circuits to develop efficient neuromorphic hardware, tailored to target tasks. In detail, you will: develop circuit-plausible training/inference algorithms and analyze in
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strong interest in research. A proven track record of scientific work, such as prior publications, is beneficial. We particularly value a solid theoretical foundation in 𝗺𝗮𝗰𝗵𝗶𝗻𝗲 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴