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Field
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Eligibility requirements for the position. Required Qualification: Ph.D. in bioinformatics, computational biology, statistics, computer science, or related field Proficiency in R or Python Minimum one year of
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assembly, population genetics, statistical genetics, complex trait mapping, and high throughput sequencing genome and programming proficiency in R, Python, Perl, C/C++, Java, and SAS are highly desirable
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experience in protein dynamics studies. The candidate should be knowledgeable about concepts in statistical thermodynamics, in python scripting and C++ programming. Preferred qualifications: Familiarity with
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and Knowledge: Strong interest in (or be already skilled in) the development, application, and testing of hydrologic models. Comfortable with working in the python programming language. Knowledge and
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. Experience in Python code, Matlab, and LabChart. Knowledge of cardiovascular physiology. Department Contact for Questions Miranda Lockwood, SHRM-CP Human Resources Business Partner mjlockwo@iu.edu Additional
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degree in physical sciences, biochemistry, or computer science is required at the start of the position (we accept ABD applicants). Applicants with prior experiences with Linux command line, Python
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assistants • Write scientific publications and present findings Required Qualifications • MA in computational social science, digital humanities, computer science, or related field • Python proficiency
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Research Associate, Translational Research Fellow - Dept. Ophthalmology Visual & Anatomical Sciences
and application, CRISPR/Cas mutagenesis, and single-cell RNA sequencing is highly preferred. Proficiency with relevant data analysis and visualization tools (e.g., R, MATLAB, or Python) is required
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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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, 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