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Field
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experience developing deep learning models using frameworks using PyTorch and possess strong Python programming skills. Experience working with Remote Sensing datasets and geospatial technologies such as GDAL
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, including data ingestion pipelines, database design, and scalable API development Write, review, and maintain production-grade Python code focused on infrastructure, system services, and integration layers
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results to validate in silico predictions Applying data analysis and scripting tools (e.g. Python, structural biology tools) to process and interpret datasets Maintaining robust data management practices
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shapes, interfaces and assembly properties. You will build and maintain Python-based workflows for generating, evaluating and iterating protein designs. This will include implementing design constraints
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analysis, or a closely related discipline. Data-science, quantitative or computational skills for analysing complex evidence or datasets. Programming skills in Python, R or related tools. Experience using
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, Resource scheduling, Libraries & Frameworks: Python, PyTorch, NumPy, SciPy, Pandas, discrete-event simulation, Anaconda, Jupyter, Systems evaluation: statistical analysis and performance metrics (e.g
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Science or equivalent Working knowledge of Matlab/Python or equivalent. Experience with programming microcontrollers and with machine learning/AI is a plus. Being familiar with laser powder bed fusion
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should be proficient with Python, the Pandas data analysis library and a data visualisation library such as Matplotlib, Seaborn, Plotly etc. Also Desirable: Proficiency with Text analysis in Python using
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using python, MATLAB, etc. Ability to support organisation of webinars and remote and in person training activities Publications in Q1 journals on the above topics Please see the attached job description
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localization Backscatter or wireless communications Statistical signal processing Software-defined radio and experimental wireless systems Python, MATLAB, C/C++, GNU Radio, or comparable research tools Previous