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Field
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understanding of human genetics. Knowledge of DNA and RNA sequencing analysis, of programming languages such as R, Python, or Bash script, and of bioinformatics pipelines for genomic data analysis is essential
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. Additional Qualifications: • Theory: Expertise in quantum optics, quantum information science, or quantum field theory. • Simulation: Proficiency in MATLAB or Python for simulation/modeling and data analysis
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characterization (SEM, TEM, XPS, FTIR, etc.) Programming skills (Python, MATLAB, or similar) Exposure to machine learning methods (e.g., Bayesian optimization, active learning) is an advantage Understanding
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, or unsupervised learning methods. Proficiency in Python and familiarity with scientific computing libraries such as PyTorch, TensorFlow, Pandas, NumPy, and related ML frameworks. Experience with large datasets
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highly skilled Postdoctoral Fellow with a proven dual‑mode research profile capable of independently performing laboratory experiments and coding predictive AI models in Python to forecast biomaterial
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Proficiency in programming languages such as C, C++ and Python We regret to inform that only shortlisted candidates will be notified. Hiring Institution: NTU
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, Python, or equivalent will be an advantage. Prior experience in laboratory testing, data analysis, or industry-related engineering projects will be an advantage. Key Competencies Ability to build and
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Python or other equivalent programming languages. Strong foundation in data analytics and data-driven modelling. Able to build and maintain strong working relationships with people within and external
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analysis is essential. Familiarity with additional omics technologies (e.g. RNA-seq), programming languages such as R or Python, and knowledge of breast cancer biology are highly desirable. You will be
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approaches. Familiar with common scientific programming languages such as python, C++, or Fortran. Experience with high performance computing environments is welcome. Candidates who do not strictly meet these