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- 
                Field
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                positively to a diverse academic community. DESIRED CHARACTERISTICS Proficiency in at least one programming language (e.g., Python, C#, or Ruby) and platforms commonly used in digital forensics and backend 
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                experiment codebases (prefer Python). Apply causal inference and discovery frameworks to clinical questions. Translate proposed methods and frameworks into real-world clinical workflows. Contribute to grant 
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                analyzing numerical methods and/or machine learning methods for scientific computing. A strong computational background and experience with languages and frameworks such as Matlab, Python, NumPy/SciPy 
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                five years. Proficiency in at least one of Python, C++, Fortran, or Julia. Ability to work effectively in an interdisciplinary team. Demonstrated written and oral communication of candidate-led results 
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                , or a related numerical field. Programming experience in one or more of: Python, C++, Fortran, Julia. Hands-on experience building and training AI models with frameworks such as TensorFlow or PyTorch 
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                (e.g., Python, C#, or Ruby) and platforms commonly used in digital forensics and backend development. Familiarity with software development lifecycle including design and documentation of software 
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                /Robotics or a closely related discipline. You will have an extensive background in coding (e.g., python, C++) and have some works published in top-tier conferences/journals. Candidate must have prior work 
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                Max Planck Institute for Heart and Lung Research, Bad Nauheim | Bad Nauheim, Hessen | Germany | 24 days agodesirable Expertise in RNA biology, mitochondria, or stress response will be considered a strong advantage Familiarity with programming languages such as R or Python for data analysis is beneficial Excellent 
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                AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 25 days agolooking for a motivated researcher with a PhD (or near completion) in fungal genomics or a related field, proven research output, and strong computational skills (Linux, Python, R, HPC). You’ll bring 
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                optimization. Practical experience with industrial or collaborative robotic arms (e.g., UR, KUKA, ABB). Proficiency in programming languages such as Python, C++, and ROS. Experience working on interdisciplinary