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Field
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CRISPR/Cas9 or other genetic perturbation approaches* For computational scientist : previous experience with NGS data analysis; fluency in R, Python or C++ Track record of writing papers as evidenced by
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. Laboratory experience analyzing coastal sediments and interpretation of results. Proficient in statistical analyses and modelling using relevant software (e.g., R, MatLab, Python etc.). Skilled in Microsoft
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(Python, MATLAB, JMP) and technical documentation. Strong analytical skills and attention to detail. Excellent written and verbal communication skills. Resourceful, meticulous and problem-solving attitude
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properties of thin film samples - Use open-source (python) fitting methods to constrain structural models, determine uncertainties, and combine these properties into a hybrid metrology digital wafer - Perform
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and statistical skills, with proficiency in R or Python Experience working with longitudinal data, infectious disease epidemiology, or high-dimensional datasets Demonstrated track record of peer
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Strong analytical, research, and scientific writing skills Proficiency in Python for modeling and machine learning applications Effective communication, teamwork, and presentation abilities Self-motivated
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Qualifications* Experience with mass spectrometry (especially DIA) and proteomics applications. Strong programming skills (Python, Java) with proficiency in a Linux environment. Experience with computational
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algorithms Python and relevant libraries (e.g., PyQt, OpenCV, NumPy, scikit-learn), particularly for developing Windows desktop application software incorporating deep learning models Hold at least a
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systems or autonomous AI frameworks · Solid foundation in computational biology · Proficiency in Python and modern ML frameworks (e.g., PyTorch, JAX) · Strong analytical, problem solving, and communication
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and Python. Contribute to project management, presentations and publications of research work. Provide technical support and establish work procedures to ongoing research projects. Perform other related