Sort by
Refine Your Search
-
Program
-
Field
-
cleaning lab dishware. Field work ranging from routine sensor maintenance, data downloads, and sensor installation, often requiring long days in the field, carrying heavy objects on uneven terrain, and
-
engine. Algorithm Development: Contribute to designing, prototyping, and testing algorithmic models for personalized content recommendations. System Evaluation: Support the evaluation of the recommendation
-
relationships; medical and community partnerships; and real time ecological momentary assessment of health via data from sensors, accelerometers, and smartphone technology. The successful candidate will join a
-
Scientific Machine Learning. The successful candidate will develop and deploy state-of-the-art SciML algorithms in high-performance computational physics codes. We accept applications from all candidates with
-
research involving biological data analysis and modeling of biological systems. In particular, they will develop and apply algorithms to construct discrete dynamic models of signal transduction networks
-
experience with data annotation and labelling, as well as understanding of (coursework) in machine learning algorithms Schedule: up to 20 hours per week Compensation: The starting rate for this job is $15
-
REQUIREMENTS: List of Responsibilities/Job duties: Research focus: Socio-technical and legal impacts of datafication and AI on communities, especially worker groups and including black-box algorithms and large
-
occupant harm from exposure to indoor bioaerosols. Key Responsibilities Responsibilities include, but are not limited to: Developing and analyzing new HVAC control algorithms to balance energy efficiency and
-
of the following: quantum field theory, quantum information, out-of-equilibrium dynamics, theoretical cosmology, particle physics, gravity, or quantum algorithms. Candidates are expected to demonstrate
-
investigate AI/ML algorithms to deliver behavioral interventions at the moments of need and how those can/should be modified to account for personalized preferences. To accomplish this goal, we study behavior