1,558 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "Université de Bordeaux " positions in Germany
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command of written and spoken English • Experience with qualitative research methods is an asset • Good knowledge of machine learning /data mining in science • Good programming skills in at least one
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(RCB), the research focus “Ribonucleases” (https://go.ur.de/rna-biologie ) and the Regensburg Center of Ultrafast Nanoscopy (RUN) also provides a wide range of opportunities for collaboration. Active
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fully taught in presence on campus. We do not offer online or distance learning in the programme. We expect doctoral researchers to be based in Hamburg. Application deadline New doctoral candidates
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, live and enjoy life to the fullest. Here is an example: https://www.gamechanger-campus.de/en/cost-of-living . Funding opportunities within the university Yes Description of the above-mentioned funding
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are processed through the online application portal: https://uni-goettingen.de/en/532016.html Language requirements Good proficiency in English and/or German is required. Applicants must provide proof
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allowance Scholarship holders are also invited to apply for different Summer Schools in Germany (four weeks) Further Information about the Universidad Nacional San Juan http://www.unsj.edu.ar/ Further
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’ political preferences identified through content analysis (https://manifestoproject.wzb.eu ). The WZB Berlin Social Science Center is a publicly funded research institution that conducts cutting-edge theory
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by colloids, as well as methods for immobilizing these ions. Modern methods of theoretical chemistry (first principles, kinetic Monte Carlo, machine learning) will be applied to investigate diffusion
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submit your application documents, including your CV, a cover letter, relevant transcripts, and contact information for references. For any inquiries, please visit our web page https://ralser.group
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, non-linear contact interactions, and varying surface conditions. Reinforcement learning (RL) offers a promising approach to develop adaptive and robust control policies, but training on physical