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Field
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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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, Java) with proficiency in a Linux environment. Experience with computational pipeline development. Statistical analysis and data visualization skills. PhD Michigan Medicine conducts background screening
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). - Scientific development tools (Linux, Git, experimental methods). Desired Assets - Experience in marine robotics, drones, or embedded systems. - Knowledge of AI applied to perception or decision-making
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Fundación para la Investigación Biomédica del Hospital Gregorio Marañón (FIBHGM) | Spain | 9 days ago
Linux environments and the use of version control systems (Git). Familiarity with handling and processing large volumes of data, complex data structures, and workflow automation is desirable. Experience
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-on experiences in software design and implementation using Python, C/C++, and Matlab, under Windows and Linux environment, Strong communication skills, and ability to work independently and with
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publications Assist in supervising research students in the group Job Requirements: PhD degree in microbiology, bioinformatics, computational biology or a related field. Expertise in python, linux and HPC. Have
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scientific conferences/journals. Qualifications: Ph.D. in genomics/computational biology/bioinformatics/statistics/computer science or related discipline Experiences in Unix/Linux shell Proficient in at least
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equipment, electronics and sensor integration, and working effectively within multidisciplinary teams. Experience with mobile manipulator robots, Linux, ROS/ROS2, algorithm design, and laboratory automation
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students in the group Job Requirements: PhD degree in microbiology, bioinformatics, computational biology or a related field. Expertise in python, linux and HPC. Have experience in conducting wet-lab
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of applications will begin immediately and will continue until the position is filled. Experience in statistical programming (R, Unix, Linux, etc.) is recommended. Experience or past training in epidemiology is not