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Field
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dimensionality reduction as well as analysis of blood proteomic data. We are looking for a student with experience in bioinformatics and relevant statistical methods using R or Python languages. Some knowledge of
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Matlab, Python, Fortran or C/C++) will be beneficial. Applicants whose first language is not English require an IELTS score of 6.5 overall with a minimum of 5.5 in all sub-skills. The studentship covers
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(sequence homology- or protein structure-based) Familiarity with UNIX/LINUX-based operating systems and shared compute infrastructure Proficiency in Python, R, or similar languages for data analysis
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Infrastructure resilience under multi-hazard scenarios Model development and data analyses includes writing well-documented, reusable code (Python or R) Collaborate closely with fellow PhDs and project partners in
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other relevant fields. You have programming experience in Python and/or R (e.g. scikit-learn, PyTorch, TensorFlow). You have knowledge of omics technologies, ideally mass spectrometry and chemometrics
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experience of programming (e.g., Python, C#, C++). Ability in teamwork and to work both independently and in groups. English language proficiency. Personal characteristics such as structured approach
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· Programming skills in Matlab, R, and/or Python · Experience in the organisation of field campaigns Language skills · Fluency in English, both oral and written. Your LIST benefits
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the application of machine learning (ML) methods or large language models (LLMs) Proficiency in Python programming and confident use of Unix/Linux environments; ideally experience with version control systems (e.g
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proficiency in Python and experience with ML/DL frameworks like PyTorch or TensorFlow Strong analytical and communication skills, creativity, and the ability to work independently while collaborating in a team
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of testicular tissue Validate gene expression at the protein level via IHC and Western blotting Analyze large-scale transcriptomic data (R, Python) Test allele-specific regulatory activity using luciferase