125 machine-learning-"https:" "https:" "https:" "https:" "https:" "UCL" "UCL" positions at Nature Careers in Germany
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service or the time stamp on the email server of TUD applies), preferably via the TUD SecureMail Portal https://securemail.tu-dresden.de by sending it as a single pdf file toiak@mailbox.tu-dresden.de or to: TU Dresden
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of English language skills by January 8, 2026 (stamped arrival date of the university central mail service or the time stamp on the email server of TUD applies), preferably via the TUD SecureMail Portal https
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and two reference contacts until the 15th of December online via (Shortlink to applyform) https://mtj.jobs/3322095 For further inquiries, please contact: sandra.schickinger@uniklinik-freiburg.de General
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the usual documents until 1/11/2026 on the application portal of the university using this link: http://obp.uni-goettingen.de/de-de/OBF/Index/76205 . For more information get in touch with Serena Müller
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. Responsibilities include: Managing and mentoring a multidisciplinary team of machine learning and image analysis experts Coordinating DCU activities across partner sites and aligning them with HI strategy Co
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of artificial intelligence, machine learning and/or deep learning experience in scientific publishing and presenting research results knowledge or experience in public health research Personal skills Independence
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biophysics, computational biology, mathematics in the life sciences, computer science and machine learning with application to biological systems, and related areas. What we provide The CSBD provides fully
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outstanding researchers with a strong track record of advancing the state of the art in machine learning and potentially its application to biology and biomedicine, with the ambition to build an internationally
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the transfer of new ideas from the lab to real-life applications, improving lives. The Theis Lab at the Computational Health Center is internationally recognized for pioneering methods in machine learning
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Professor (W3 / W2 with Tenure Track to W3) for Materials and/or devices for Photonics and Quantum T
quantum technologies. This research can be complemented by digital methods of process simulation and optimization, as well as machine learning. Requirements include an outstanding PhD in materials science