-
) -POSTDOC [#30377] Position Title: Position Type: Postdoctoral Position Location: Berkeley, California 94720, United States of America [map ] Subject Areas: Astrophysics / Astrophysics Cosmology/Particle
-
experience in software development. Experience applying large language models (LLMs) or autonomous agents to scientific tasks such as code generation, protocol reasoning, or automated experimental planning
-
. This position is expected to pay between $137,916 to $142,053 annually. Actual salary will depend on the candidate's overall experience and expertise, including prior experience in Postdoc roles. This position
-
UCD Center for Labor and Community - Engaged Research Fellowship Project Coordinator (PROJECT POLICY
: Monthly Salary Grade: Grade 21 UC Job Title: PROJECT POLICY ANL 3 UC Job Code: 007398 Number of Positions: 1 Appointment Type: Staff: Contract Percentage of Time: 100% Shift (Work Schedule): Monday - Friday
-
to the field. POSITION INFORMATION Salary or Pay Range: $26.82-$47.61 Salary Frequency: Bi-Weekly Salary Grade: Grade 19 UC Job Title: FIELD RESEARCHER 2 UC Job Code: 005190 Number of Positions: 1
-
. Coordinates transfer of care as applicable. POSITION INFORMATION Salary or Pay Range: $73.72 - $99.20 Salary Frequency: Hourly Salary Grade: 114 UC Job Title: CLIN NURSE 2 UC Job Code: 009139 Number
-
Grade: BYA UC Job Title: ATH PROFL 1 BYA UC Job Code: 005171 Number of Positions: 1 Appointment Type: Staff: Contract - Contract position with a 12-month term Percentage of Time: 0.00% Fixed Shift (Work
-
less than 3 years of paid postdoctoral experience. Salary for Postdoctoral positions depends on years of experience post-degree. This position is represented by a union for collective bargaining purposes
-
less than 3 years of paid postdoctoral experience. Salary for Postdoctoral positions depends on years of experience post-degree. This position is represented by a union for collective bargaining purposes
-
research into control theory of neural population dynamics. This position has the specific focus of developing ML methods to assess the feedback controllability of neural population dynamics recorded from