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Field
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research. Preferred Skills Familiarity with nuclear structure theory, astrophysical modeling, or experimental nuclear physics techniques Experience with numerical modeling and programming (e.g., Python, C
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manipulation, tactile sensing or haptic systems Proficiency in programming (Python, C++, MATLAB, or similar) Experience with robotic platforms and hardware Knowledge of machine learning and signal processing
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research support. Responsibilities Design and print 3D models, develop Python code, perform experimental spectroscopy tasks, analyze images through Python, write papers, and present research at conferences
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Experience with digital modelling tools and platforms for power and energy systems (e.g., EnergyPlan, DIgSILENT, or similar). Strong programming skills in Python, MATLAB, or similar environments are required
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-driven applications. Demonstrated expertise in designing, implementing, and evaluating complex software systems. Strong programming skills in relevant languages (e.g., Python, C++, Java) and experience
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skills: Experience in statistical programming in languages such as R (ideal) or Python. An understanding of linear models and probability. A background in biology, with a preference for cellular biology
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Python, R, Java, or Matlab. Desirable: Experience of research in analysing healthcare data (e.g. EHRs). Evidence of collaboration with industries, policy makers, or institutions. Demonstrable ability
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robotics) for field-based phenotyping Data management and analytics from multi-stream remote sensing platforms Preferred willingness to learn: Use of Python, CRBasic, Matlab, C++, R, or other programming
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by 9/1/2026. Preferred skills: Experience in process-based crop, soil, or hydrological modeling. Proficiency in Python and other programming languages (Fortran and C/C++ are a plus). Familiarity with
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related to agriculture, soil, water, environment, or engineering Experience with GIS, R, Python, Matlab, and similar advanced software platforms is desirable Experience with data organization, data