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several students from abroad in our master’s program each year. It is important to us to provide a family-friendly environment at ESAGA. The university has several offers regarding child care for children
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the structured Junior Faculty Development Program and have the opportunity to teach at LMU Munich engage with international top-class economists within our CESifo network with over 2,000 members from all over
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to contribute to groundbreaking work in our research area. About the Program: We are implementing a program that creates an additional two year postdoctoral position exclusively for female researchers working in
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student assistants and contribute to shaping the CRC’s research direction Your Profile PhD in computer science, neuroscience, machine learning, or related field Strong programming skills in Python and
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for laboratory and field work Strong background in programming and data analysis (preferably Python) Excellent data analysis and publication capabilities Excellent communication skills in English, both written and
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engineering methods (e.g., via CRISPR). Plan and execute experiments to probe robustness of tissue morphogenesis, particularly through quantitative imaging and large-scale molecular profiling (e.g., via scRNA
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-Scripting very good knowledge in programming, preferably in Python,Fortran, Matlab or R experience in the environment of High Performance Computing (HPC) is desirable, but not mandatory capability to work in
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development. Experience with implementing statistical learning or machine learning (e.g. Bayesian inference, deep-learning). Programming skills in Python and experience with frameworks like PyTorch, Keras, Pyro
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language processing (NLP), and fine-tuning techniques Familiarity with structured reasoning, chain-of-thought processes, and agent-based systems is beneficial Strong programming skills (preferably Python); experience
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technologies to fundamental physics questions. The advertised positions will be part of the project “QS-Gauge: quantum simulation of lattice gauge theories”, funded by the Emmy Noether programme of the DFG