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Field
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principles. The candidates must also be able to quickly grasp emerging trends in the relevant discipline. The candidate should be willing to work using different programming languages/frameworks such as Python
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analytical socio-technical skills, including statistical analyses Proven programming experience using Python, R, or others (We will not consider applications that do not showcase that) Having experience
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(e.g., Python, or MATLAB, or C++; knowledge in ROS). Interest in robot control, learning, manipulation, and task planning. Preferred Experience with robotic hardware or simulation tools. Publications in
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: university and, if applicable, PhD degree (e.g. Master/Diploma) in mathematics, physics, materials science or related subjects basic knowledge of computer programming (e.g. Python, Matlab and C++) excellent
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project focus. Technical computing skills: Strong programming skills (e.g. Python, C++, MATLAB). Experience with robotics software frameworks such as ROS, Gazebo, or other simulation environments is
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sensors (sonar, camera, inertial units) and their limitations would benefit this project’s focus. Technical computing skills: Proficiency in programming (e.g. Python and C++). Experience with robotics
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, ecosystem function measurement); Basic skills in satellite image analysis; Affinity and experience with data analysis and visualization in R, Python or equivalent; Excellent English language skills, both
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strain engineering is a plus. Data analysis skills (e.g. in Python, MATLAB or similar) are a plus. Excellent communication skills in English, both written and spoken Strong motivation to work
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(e.g. C++, Python, Matlab) OpenFOAM (beneficial, not required) Strong analytical and problem-solving skills. Approval and Enrolment The scholarship for the PhD degree is subject to academic approval, and
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qualifications A masters degree in neuroscience, physics, evolution and ecology, or related quantitative fields. Prior experience with Python or Matlab, and a willingness to learn analysis tools. Excited about