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computational approaches Beyond technical training, you will join a dynamic, collaborative and international team and receive structured support through our PhD training program. Your Profile: Master’s degree
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play a central role in this interdisciplinary initiative. They will: Develop and apply machine learning (ML) methods – including surrogate modeling, feature extraction, and inverse design algorithms
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Research Associate / PhD Student (m/f/x) (subject to personal qualification employees are remunerated according to salary group E 13 TV-L) starting at the earliest possible date. The position is limited to 3
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the umbrella of the Dresden International PhD Programme (DIPP) Teaching language English Languages All courses are held in English. The primary language in the labs is English. The PhD thesis is written and
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science and information science techniques. Several areas of computer science and mathematics play important roles: data management and engineering, machine learning and data analytics, signal and image
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Collaborative Doctoral Project (PhD Position) - AI-guided design of scaffold-free DNA nanostructures
degree of independence and commitment Experience with machine learning and high-performance computing is advantageous, but not necessary Our Offer: We work on the very latest issues that impact our society
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-time basis for a duration of up to 3 years, with the possibility of part-time work. The position includes the opportunity to pursue a doctorate (PhD) at TU Clausthal. With these positions, we invite YOU
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between quantum computers (via Qiskit) and classical HPC resources Validate the QCS-MiMiC implementation on IBM’s ibm_cleveland quantum computer by reproducing recently published benchmark QM / MM
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Degree Dr rer pol or PhD Course location Berlin Teaching language English Languages All courses, workshops, and other events are held in English. All communication within the programme is in English
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QCLs) for high-resolution spectroscopy. Within the framework of the priority program INtegrated TERahErtz sySTems Enabling Novel Functionality (INTEREST) funded by the German Research Foundation (DFG