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Field
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. Applicant should have experience in time-series processing with appropriate AI models (recurrent networks, LSTM) and experience in 2D convolutional neural networks in Python. This is a part-time position (5
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2D convolutional neural networks in Python. This is a part-time position (5 hours/week) funded until 31/03/2026 with a possibility of extension and is suitable for a Ph.D. student with relevant
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activity: Spatial analysis in GIS (e.g., in QGIS or Python) aimed at analysing spatial relationships between data represented as vectors and rasters. WE REQUEST Professional education, qualifications and
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methods Good knowledge of object orientation and at least basic knowledge of UML Knowledge of minimum one programming language (e.g. C++, Python, Java) Experience with the Robot Operating System (ROS) Good
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prerequisite (i.e., familiarity with linux, bash, conda, python). Experience in molecular dynamics simulation, protein chemistry or phylogenetics would be major assets. An interest in developing wet lab skills
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/PhD) or related field. - Simulation & data: TRNSYS (or similar), time-series processing; Python (pandas/numpy). - Experience with GIS and/or climate/solar datasets (e.g., METEONORM, PVGIS
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the position description. Preferences The ideal candidate will have experience with wearable sensors and/or remote monitoring approaches and strong programming (e.g., R, Python, or similar) and writing skills
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University of Massachusetts Medical School | Worcester, Massachusetts | United States | about 2 months ago
modeling, or machine learning - Experience with large-scale genomic data analysis (e.g., GWAS, QTL, PRS, or multi-omics integration) Strong programming skills in R or Python; familiarity with Bayesian
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microfluidics, kinetic data analysis, Python scripting, protein purification, and cell culture are beneficial The candidate should have an interdisciplinary aptitude, strong organisational and interpersonal
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development (experience in multiple fields are considered beneficial). Familiarity with simulation software and numerical methods and proficiency in programming languages (Rust, Python, MATLAB, C/C