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and needs. We value work-life balance and well-being in all aspects of life. We work in a hybrid model, with the primary workplace located at the Otaniemi Campus in Espoo, Finland. Life on
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modelling; strong programming and research engineering ability (Python with modern ML tooling such as PyTorch/JAX) and good software practices; familiarity with interactive/agentic settings (e.g., tool-using
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Postdoctoral Researcher in ML for Dynamical Systems Representation, Prediction, and State-estimation
for predictive modelling and state estimation for fundamental applications within physical sciences. Your role The main research responsibilities involve building cutting edge machine learning techniques
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in crystal synthesis, characterisation and modelling to study and generate a new understanding of MoSS. These advances will have applications across multiple sectors, including pharmaceuticals
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modelling; strong programming and research engineering ability (Python with modern ML tooling such as PyTorch/JAX) and good software practices; familiarity with interactive/agentic settings (e.g., tool-using
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viewing conditions and across languages. By combining behavioural methods with machine learning, it aims to develop physiologically-based models of lexical colour categorisation. This is a multidisciplinary
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the Finnish Center of Excellence in Quantum Materials . Your role and goals The research will focus on developing and using machine learning algorithms to discover novel materials and to build generative models
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are seeking a highly-motivated and ambitious researcher with a strong background and experience in RF/microwave engineering, additive manufacturing, and AI modelling to work on cutting-edge research in
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with other researchers to translate these experimental results into our numerical models, helping to improve their predictive capability. You will help ensure a healthy and vibrant research environment
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: combining microscopic modelling and simulations (e.g., Brownian dynamics) with continuum approaches (e.g., statistical field theory) to study the macroscopic behaviour of proliferating active systems such as