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Field
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. Proficiency in programming languages and analytical tools such as R, Python, and machine learning frameworks. A strong track record of research outputs, including publications in high-quality peer-reviewed
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, Ansys, or comparable simulation software. Knowledge of RF/MW propagation and bioheat-transfer modeling. Experience automating image-processing or simulation workflows using Python, MATLAB, C++, or similar
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use of software such as R, Python, or similar analytical tools, are helpful. Exposure to modeling water or nutrient dynamics, studying low-water-requirement or salt-tolerant crops, or evaluating
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(Kubernetes), serverless computing, and REST API development. Proficient in Python, with basic experience in machine learning or computer vision libraries; familiarity with Vision-Language Models (e.g., CLIP
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Python and/or C++. Demonstrable experience with machine learning frameworks (e.g., PyTorch, TensorFlow). Hands-on experience with game AI agents and/or GUI agents such as Mineflayer, Unity ML-Agents
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Mechanical Engineering/AI Soft skills: Presentation, Research Lead Hard skills: Experience with Python/AI programming, Research approach development etc. Experience: Experience and domain knowledge in
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learning for materials discovery or quantitative image analysis, DFT calculations for catalyst design, experiences with MATLAB / Python / AutoCAD / COMSOL • Organic synthesis, polymer chemistry, synthesis
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, San Francisco, and Berlin. The successful candidate will be resourceful with the ability to act on their own initiative, excellent quantitative skills including programming (e.g. Matlab, R or Python
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. Analytical and Computational Skills: Demonstrated ability to analyse complex suspension flows, with proficiency in scientific programming (Python or MATLAB) being highly valued. Research Excellence: A strong
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within the team and the customers. Be self-directed to fulfil the project requirements. Job Requirements: Competence in working with languages such as C along with AI applications as well as Python-based