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algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC) to accelerate design iterations Integrate ML approaches with finite
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around 15 are PhD students. The work environment is open and welcoming, striving to provide each employee with the opportunity to develop personally and professionally. The field of solid mechanics relates
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significant role in learning in AI by enabling cognitive agents to acquire actively knowledge and skills through interaction with their surrounding environment. Embodied AI requires tools, algorithms, and
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environment project, we will develop automated species and community recognition, particularly focusing on pathogenic soil fungi, with help of deep-learning algorithms fed with microscopic image and Raman
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collaboration with other researchers. Your profile • Formal requirement: Doctoral degree (PhD) in quantitative genetics, tree breeding, biometrics, statistical genetics, bioinformatics or related field
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110 PhD students. The Department of Oncology-Pathology is responsible for undergraduate courses in Pathology, Oncology and Forensic Medicine for medical students, as well as for Tumor biology courses
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in their computation. We want to understand the fundamental principles that permit us to build privacy-aware AI systems, and develop algorithms for this purpose. The group collaborates with several
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). Meritorious: It is also an advantage if you have experience with: Machine learning. Coupling algorithms of fluid-structure interaction solvers. Computational aeroacoustics. Swedish is not required
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of computational fluid dynamics (CFD). Knowledge of finite element method (FEM). Meritorious: It is also an advantage if you have experience with: Machine learning. Coupling algorithms of fluid-structure interaction
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computational algorithms to enable regenerative cell therapies. Now, we are seeking a highly driven postdoctoral researcher to contribute to our ambitious mission. Division The Division of Biomolecular and