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; significant practical experience in 3D image analysis or computer vision; knowledge and experience in scientific programming (python (preferred), Matlab or other relevant language) with application to image
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, or similar. Good knowledge in programming (e.g. C or python) Experience in 3D image segmentation. Track record of producing high-quality research Documented pedagogical skills and pedagogical training
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of Python language Knowledge in XRD and/or XRF analysis. Eligibility Appointment to the position of postdoc requires that the applicant has a PhD, or an international degree deemed equivalent to a PhD, within
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degree in relevant fields (bioinformatics, immunology, computational biology, mathematics, and/or statistics). Strong programming skills in R and/or Python Demonstrated strong ability in analyzing high
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publication record in reputable peer-reviewed journals is highly desirable. Proficiency in programming, particularly in R, Python, or other relevant languages, is required. Qualified candidates should also meet
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excellent skills in modern computer programming languages such as C++, Python, MATLAB or R. We look for candidates who enjoy collaborating in interdisciplinary teams and are good at communicating science in
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degree in relevant fields (bioinformatics, immunology, computational biology, mathematics, and/or statistics). Strong programming skills in R and/or Python Demonstrated strong ability in analyzing high
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programming languages (e.g., Python, R). Experience working in a LINUX/UNIX environment. An excellent molecular biology skillset. Experience with NGS library preparation supported by a strong publication record
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communication skills in English are required. Assessment criteria: Good programming skills (e.g., C++, Python, Julia), knowledge of the most common frameworks, e.g., Tensorflow and JAX, and cloud platforms/deployment
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bioinformatics, physics, statistics, computer science, computational biology, or related fields. Experience programming in Python (or R) as well as bash/shell scripting. Experience with machine-learning and deep