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technical field OR a combination of education and relevant working experience to equal at least four years Strong programming skills in Python. Familiarity with machine learning, deep learning, and
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familiarity with large datasets such as proteomics or sequencing. Experience in epigenetics or gene regulation is a plus. Experience with statistical analysis tools such as R or Python is required (Candidates
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that is reflected in applicants' publication record. Skills and Experience: Programming in Python (must), Image processing (desirable). Basics of Si Microfabrication and familiarity with lithography
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genomics and novel therapies. As a successful candidate, you will: Analyze genomic and proteomic data and generate expression matrices using preexisting code. Write short Perl/Python scripts to support
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Research experience in developing machine learning and/or deep learning methods. Essential Application/interview Programming experience in Python and use of relevant machine learning / deep learning
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, Electrical Engineering, or a related field. Strong foundations in machine learning, deep learning, computer vision, and at least one of 3D/4D vision, reinforcement learning, or robotics. Proficiency in Python
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knowledge of Python and NLP concepts is a must. Experience with LLM Inference frameworks (i.e., Ollama or vLLM) is a must. Experience with Generative AI and LLMs (i.e., Llama, Gemma, Qwen, etc) is a must
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or Knowledge: Significant experience developing code in Python with knowledge of Node.js and/or a compiled language such as C/C++. Preferred Competencies Strong analytical skills and problem solving
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, electronics, telecommunications, photonics, microwaves engineering, physics or similar Knowledge of simulation tools for transmission systems, digital signal processing; experience in MATLAB/Python. Theoretical
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Mathematics, Operations Research, Engineering, or a related quantitative discipline. A strong foundation in stochastic or distributionally robust optimization is required. Proficiency in Python with experience