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Field
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microscopy, antibody-based techniques, small molecules/ligand-trap based therapies Preferred qualifications Experience with bioinformatic analysis using R and/or Python. Experience with molecular/cellular
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, environmental sciences, geoinformatics, or a related discipline. Proficiency in advanced learning techniques and statistical modeling. Strong programming skills in languages like Python or R. Professional
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required. Substantial experience in machine learning, Python and R programming, and familiarity with deep learning packages (e.g., TensorFlow, Keras, or PyTorch) are essential. Additional Qualifications
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; sound programming skills, with a strong preference for MATLAB; experience in other scientific programming languages (e.g. Python, R) is also valued; familiarity with international macroeconomic and trade
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/ML/CV venues Proficiency in Python and deep learning frameworks Experience in machine learning, computer vision, or NLP Strong communication and collaboration skills Our commitment to inclusion and
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example of previous publications where the candidate performed such work. ● Generate user friendly scripts in R, and Python for data visualization and analysis that can be used by other team members
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or tools and methodologies for dynamical simulation. programming skills in Python, MATLAB, Modelica and/or domain specific tools used for energy system modelling and simulations. Emphasis is also placed
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. Proficiency in algorithm development using Python will be advantageous Where to apply Website https://www.timeshighereducation.com/unijobs/listing/407953/research-fellow-ai-… Requirements Additional Information
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datasets using Python or R. Ability to work both independently and collaboratively, with strong organisation, attention to detail and communication skills. Clear motivation to apply interdisciplinary and
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related field. Experience The ideal candidate should have demonstrated experience in several of the following areas: Extensive experience with python and modern C++ in a Linux/UNIX environment, including