Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- Monash University
- University of Sheffield
- ETH Zurich
- University of Glasgow
- Columbia University
- Heriot Watt University
- Nature Careers
- SciLifeLab
- University of Toronto
- University of Washington
- CEA
- CNRS
- Case Western Reserve University
- Forschungszentrum Jülich
- Harvard University
- Oak Ridge National Laboratory
- Rice University
- Rutgers University
- SUNY Polytechnic Institute
- Stony Brook University
- Technical University of Munich
- University of Bristol
- University of California
- University of California, Los Angeles
- University of California, San Diego
- University of Miami
- University of Nebraska–Lincoln
- University of North Carolina Wilmington
- University of Warsaw
- Zintellect
- 20 more »
- « less
-
Field
-
parameter estimation using Bayesian inference, and/or the exploitation of Machine Learning (ML) based algorithms to reduce false positives caused by human generated interference signals in the observational
-
(for example, R, Python, or Matlab). Experience with graph modeling, Bayesian statistics, or causal inference is a plus. The candidate will join an integrated team of computational scientists, molecular
-
Skills, Knowledge and Abilities: Comprehensive knowledge of pharmacokinetic/pharmacodynamic modeling theory including model building, parameter estimation methods for individual studies (maximum likelihood
-
learning and Bayesian statistics. FLSA Exempt Grade 06 Salary Details $82,166 - $90,382 Minimum Salary 82166.000 Mid Range Salary 104002.000 Maximum Salary 125837.000 Offer Information The final salary offer
-
, specialty, and training. The above hiring range represents the University's good faith and reasonable estimate of the range of possible compensation at the time of posting. Position Summary The Center
-
and is part of a cluster hire across the School of Social Sciences. The specialty area should be in human factors/human-computer interaction (HF/HCI), industrial-organizational psychology, applied
-
analysis Developing methods to improve the accuracy and robustness of parameter estimation and uncertainty quantification using Bayesian techniques Applying the developed methods to calibrate and validate
-
-based, Bayesian or matrix factorization methods for multi-omics integration. Ability to independently perform data analysis and scientific interpretation based on omics data at an internationally
-
exploration strategies that go beyond traditional techniques such as linear programming or deterministic solvers. You will work on cutting-edge methods including: Bayesian optimization Surrogate modeling
-
Assistant Professor in Applied Statistics or Actuarial Data Science Directorate: School of Mathematical and Computer Sciences Salary: Grade 8 - £47,389 - £58,225 Contract Type: Full Time (1FTE