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Field
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learning and experience in two or more of: computer vision, sensors/sensor fusion, robotics fundamentals. • Proficient in programming languages such as Python and C++; experience with frameworks such as
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predictive checking, model comparison) • Computational modelling with Python and Dynesty, JAX, NumPyro, and PyTorch • Use of asteroseismic and spectroscopic survey data (e.g. PLATO, Gaia, APOGEE, TESS) • High
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analytical programming language (e.g., Python, R) or a universal programming language (e.g., C#, Java, C++, Rust) Knowledge of the use of relational and non-relational databases Very good English skills
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 14 days ago
in association or cooperation with one or more R&D units, or be enrolled at the date of signing the scholarship contract in a doctoral program; c) proficiency in Python and/or C++. Additional
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PhD Studentship: LLM-Based Agentic AI: Foundations, Systems & Applications – PhD (University Funded)
. Proficiency in programming and modern ML tooling (e.g., Python, PyTorch); experience with LLMs (e.g., using Hugging Face libraries) is a plus. Ability to reason about complex systems and turn ideas into code
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characterisation techniques is beneficial, but not required; Experience in at least one programming language for scientific computing (C/C++, Matlab, Fortran, Python, Julia, ...); Good communication skills and
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modelling; Knowledge of spectroscopy is beneficial, but not required; Experience in at least one programming language for scientific computing (C/C++, Matlab, Fortran, Python, Julia, ...); Good communication
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with experience in causal inference using panel data (e.g., Difference-in-differences) solid knowledge of Stata, R and/or Python for conducting econometric analysis previous knowledge of conducting
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a relevant subject (computer science, mathematics, or related subject) Proficiency in English (both oral and written) Python programming skills. Solid mathematical background is desirable. Studentship
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or related degree. Curiosity, resilience, and an interest in interdisciplinary, impact-driven research are essential. Experience with ecological fieldwork, data analysis (e.g., R or Python), or public