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Field
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required: Programming (e.g. Java, Python, Haskell, C, PHP, JavaScript, SQL, and covering data structures and algorithms, concurrency, software architecture, design patterns). Theoretical computer science
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or similar. Running social simulations with AI agents using platforms like Concordia or similar. Coding in Python or a similar language for simulation, visualization, and advanced statistical analysis (causal
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Basic, Python, or similar technical computing tools • Experience with interdisciplinary or project-based learning models • Commitment to STEM education Instructions and Required Materials for Application
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in the engineering classroom Preferred Qualifications • Prior experience teaching first-year engineering or computing students • Familiarity with MATLAB, Visual Basic, Python, or similar technical
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programming skills in Python, MATLAB, C++, or similar scientific computing environments, including high-performance and GPU computing. A strong scientific track record, evidenced by high-quality publications
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4–5). Key areas include but not limit to Python programming and discrete structures. Appointments will be commensurate with experience and qualifications reflecting a record of demonstrated ability
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, and participation in departmental and college committees. Areas of expertise may include computer theory, systems design and programming, introductory and intermediate programming in Python, Java, C
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developing optimization-driven approaches to multimodal device tailoring. We are looking for someone with A PhD in Human-Computer Interaction or a closely related field Strong programming skills (e.g., Python
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Laboratory of Computer Science, Robotics and Microelectronics of Montpellier (LIRMM) and Alternative Energies and Atomic Energy Commission (CEA) | Montpellier, Languedoc Roussillon | France | 3 months ago
mechanical modeling completed by knowledge on control are required, along with a strong interest in innovation in miniature robotics. Skills in scientific programming (e.g. Python, MATLAB, or equivalent) and
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ML domains, such as deep learning, reinforcement learning, or human-centered ML. Proficiency in programming languages (e.g., Python) and ML frameworks (e.g., TensorFlow, PyTorch), with evidence in