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Field
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ability to think critically about scientific analysis in order to ensure robust results Computational skills to include experience of using a statistical package (e.g., R, MATLAB or Python) Ability to work
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processing environmental exposure and health administration data via Application Programming Interfaces (APIs) proficiency using statistical programming software such as R, SAS, STATA and Python; and GIS
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. • Proficient experience with various robotics simulators (e.g., MuJoCo, PyBullet, Gazebo) and excellent programming skills in C++, Python, and MATLAB with the ability to develop efficient, production-quality
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knowledge in modeling light propagation in non-Hermitian random media. Proficiency in programming languages such as Matlab, Mathematica, or Python. Proficiency in using electromagnetic simulation software
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time experiments. Experience of working in an interdisciplinary team. Experience with supervising and mentoring more junior researchers. Beneficial Criteria Experience in coding (e.g. Python, C, Fortran
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, Physics, Computer Science, or a related field. Hands-on experience with computational materials methods (e.g., DFT, molecular dynamics, machine learning force field simulations). Proficiency in Python
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using tools such as Python or R Applying for internal or national research funding Engaging with industry partners and academic collaborators This is a 24-month fixed term role working 37.5 hours per week
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or experience with data analysis methods (e.g. use of Stata, R, Python, or Stata) Ability to communicate complex information clearly Excellent ability to work as a team and independently including co-ordinating
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research experience. Proven track-record analysing large-scale ‘omics and/or healthcare datasets, preferably in cancer genomics. Experience of advanced coding in Python or R plus Shell scripting; familiarity
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cancer genomics and functional interpretation of genetic variants Proficiency in Python, R, or other bioinformatics languages Knowledge of cloud computing, and high-performance computing (HPC) environments