-
competence in seismic data analysis is a requirement. Experience from or competence in computer programming (MATLAB, Python) is an advantage. Applicants must be able to work independently and in a structured
-
a requirement. Experience from or competence in computer programming (MATLAB, Python) is an advantage. Applicants must be able to work independently and in a structured manner and demonstrate good
-
skills in Matlab and/or Python are required. These should be documented, for example through a GitHub profile or similar. Familiarity with numerical methods for solving Maxwell’s equations, particularly in
-
relevant programming languages (e.g., Python, MATLAB, R) is a requirement. Familiarity with downscaling and bias correction of climate data (e.g., from CMIP/PMIP) is an advantage. Experience with
-
processing, medical/biological applications, sensor technology and sensor data, Matlab framework. The applicant must be fluent in oral and written English. Advantageous prior experience: elderly care
-
in scientific coding and data analysis programming languages, such as Python or MATLAB, is a requirement. Experience with running snowpack and/or Earth System Models is a requirement. Experience in
-
signal processing Mandatory experience and formal training: signal processing, medical/biological applications, sensor technology and sensor data, Matlab framework. The applicant must be fluent in oral and
-
or MATLAB, is a requirement. Experience with running snowpack and/or Earth System Models is a requirement. Experience in field instrumentation or other demonstration of observational data curation is an
-
. Proficiency in relevant programming languages (e.g., Python, MATLAB, R) is a requirement. Familiarity with downscaling and bias correction of climate data (e.g., from CMIP/PMIP) is an advantage. Experience with
-
, ill-posed nonlinear inverse problems Numerical optimization techniques Machine learning Strong programming skills in Matlab and/or Python are required. These should be documented, for example through a