Sort by
Refine Your Search
-
waste. The projects are highly collaborative and multidisciplinary with excellent opportunities for advanced training and scientific development. Interested candidates will possess significant experience
-
, executing, and analyzing experiments with mice investigating the consequences of neuronal circuit manipulation, training graduate students, preparing reports and presenting experimental results to the IU
-
PhD in informatics or a related discipline (e.g., computer science) · Ideal candidates will have EITHER, both are not required o Experience recruiting and retaining adolescents in longitudinal
-
, or space biology. · Experience with human analog studies or related experimental models is highly desirable. · Excellent communication, organizational, and interpersonal skills. · Demonstrated ability
-
diagonalization, tensor-network techniques (DMRG, TEBD, PEPS), or others to study impurity models. • A demonstrated publication record in theoretical quantum physics. Preferred Qualifications: • Experience
-
have a completed doctorate in higher education or related field before the beginning of the appointment. Successful candidates will bring experience working in or directly supporting higher education
-
, creative, and well-organized candidate with experience in stem cell and cancer biology, molecular biology, next-generation sequencing techniques, bioinformatics, proteomic analysis, and animal handling
-
. Proficiency in Python, MATLAB, or R. Strong quantitative and analytic skills. Preferred Qualifications Experience with evidence-accumulation models (DDM, sequential sampling, Bayesian models). Experience with
-
communication skills, demonstrated experience working with collaborative teams, and proficient quantitative and coding skills. Experience working with Earth system models, attribution science approaches
-
experience in one or more of: large-scale data analysis, time-series photometry, spectroscopy, astrometry, Bayesian/statistical inference, and/or software development for astronomical datasets. Department