Sort by
Refine Your Search
-
Listed
-
Category
-
Field
-
Monte Carlo algorithms as directed by Professor Sandeep Sharma in the Division of Chemistry and Chemical Engineering. Essential Job Duties Develop and maintain auxiliary field quantum Monte Carlo
-
Consortium’s Science Ground Segment, providing algorithm and software development, participating in data quality assurance, and performing data processing. In addition, ENSCI supports the US research community
-
-of-the-art algorithms for detecting and classifying safe landing zones using computer vision techniques in order to design and develop custom models for detecting landing zones in real-time based on drone
-
: design and implement technologies and algorithms (including feedback control design and implementation) to reduce the noise sources that limit the current detector sensitivity; model optical subsystems
-
passions will play a role in defining on which research aspect you will focus primarily: design and implement technologies and algorithms (including feedback control design and implementation) to reduce the
-
part of the diverse Caltech community. Job Summary This position involves research and evaluation of state-of-the-art algorithms for detecting and classifying safe landing zones using computer vision
-
to advance the project. The successful candidate will have extensive experience developing models and algorithms for analysis of noisy biological data, a deep background in analysis of stochastic processes
-
, algorithmic exploration, and collaborative research, rather than independent program leadership. This position is well-suited for candidates in the early stages of their career. Essential Job Duties Conduct
-
from astrometry, flat-field determinations, PSF uncertainties, and gain drifts. The applicant will also develop algorithms for quantifying best-fit flux and errors with outlier rejection in the all-sky
-
of the variability of stars. The analysis will involve processing the photometric time series data into photometric light curves and developing algorithms to quantify the variability of the stars. All data will then