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University professorship (m/f/d) in 'AI in Occupational, Social and Preventive Medicine' (salary gra
implementation of AI algorithms and tools for analyzing and predicting health-related events, process optimization and decision support in healthcare. Validation of models to ensure accuracy and reliability
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enable the digitisation of strategies for the expert. The concept is also used to describe an algorithm for the development of process parameters to eliminate laser-induced roughness during laser polishing
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automation in industry. Disruptive technologies such as artificial intelligence and quantum computing play a key role here. Fraunhofer IKS is conducting research to ensure that these applications are reliable
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Announcement for fields of study such as: Automation technology, computer science, cybernetics, mechanical engineering, mechatronics, control engineering, technical computer science, technology
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Your Job: In this Master’s thesis, you will investigate the impact of different programming algorithms on the stability of resistance states using a sophisticated 3D Kinetic Monte Carlo (KMC) model
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hours per week), based in Berlin. Your Tasks Development of software for the analysis, management, and interpretation of omics data Selection and benchmarking of algorithms, libraries, and tools
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) simulations and offer time-saving benefits. We are looking for a dedicated and motivated student to assist us in implementing a novel Graph Neural Network based algorithm that can act as surrogate for FEM and
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multi-parameter ion-beam tuning procedures (collaboration with Univ. of Vienna and HZDR) and developments of machine learning (ML)-algorithms for optimization of beam parameters and control of relevant
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Temporary Job Status Full-time Offer Starting Date 1 Feb 2026 Is the job funded through the EU Research Framework Programme? Horizon Europe - MSCA Marie Curie Grant Agreement Number 101226517 Is the Job
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students who would like to write their final thesis in the field of machine learning / computer vision. The primary goal of this master’s thesis is to develop an algorithm that can accurately and efficiently