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using Python, Matlab, or equivalent programming languages. Previous experience in interdisciplinary research projects at the interface between engineering, materials science, and biology will also be
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Experience with confocal, light-sheet and fluorescent microscopy applied in biophysics Experience in data analysis with coding (Python interface) Experience working with microfluidics and protein aggregation
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the Linux operating system, bash scripting, Git, Python, and reproducible software environments. Demonstrated expertise in writing advanced software in Python and in the design and implementation of deep
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, or a related field; Good publication record in ML, and/or computational methods for audio data. A publication record in ML applied to bioacoustics is a bonus; Good programming skills in Python
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building and managing complex relational datasets; Proficiency in Python, R or comparable analytical languages and software; Proficiency in the use of large-language models (LLMs) for quantitative and/or
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., in Python. A keen interest in interdisciplinary research. An excellent command of English, as you’ll be working in an internationally diverse community and with international partners. Ability to learn
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concepts Proficiency in R and Python Experience with cancer genomics, single-cell RNA-seq and/or ATAC-seq analysis (strongly preferred) Ability to work independently as well as collaboratively in
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highly desirable. Proficiency in programming languages such as Python or C++. Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch) and advanced data analysis tools. Excellent problem
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Proficiency in R and Python Experience with cancer genomics, single-cell RNA-seq and/or ATAC-seq analysis (strongly preferred) Ability to work independently as well as collaboratively in an interdisciplinary
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samples and myeloma cell lines. Preferred: experience with NGS analysis, R/Python, other computational languages, bioinformatic analysis. References: Mikulasova A, Morgan GJ, Walker BA (2022) Chromosomal