Duties:

Duration: 1 year, with a potential for extension based on performance (up to 2 additional years)

Job Description: We are seeking a highly motivated and skilled researcher to join our team and contribute to projects focused on understanding and improving satellite observations of Earth systems, with a special interest in storm morphology and atmospheric and surface properties. The successful candidate will play a key role in delivering global analyses of cloud distributions, atmospheric column characteristics and validation of satellite retrievals relevant to understanding of the Earth’s climate system.

Responsibilities:

• Help with development and implementation of Machine Learning (ML) algorithms and models to define links between atmospheric properties and radiances collected by satellite and ground instrumentation.
• Conduct extensive analysis of satellite- and ground-based data relevant to precipitating systems.
• Collaborate with a multidisciplinary team of scientists to integrate the developed ML methods into existing research frameworks.

Contribute to the publication of research findings in high-impact scientific journals

Qualifications:

Requirements:

• Ph.D. in Environmental Science, Atmospheric Science, Computer Science, Engineering or a related field, or MS degree with 5+ years of experience.
• Prior knowledge and hands-on experience in ML algorithm implementation.
• Proficiency in Python programming language and ML-oriented tools, such TensorFlow, and/or PyTorch.
• Good understanding of Unix/Linux OS and scripting; familiarity with common data formats, such as NetCDF, HDF5, buffer.
• Excellent skills in manipulating large volumes of data.
• Prior experience in data visualization using Python tools.
• Experience with satellite data analysis and retrieval techniques is highly desirable.
• Knowledge of hydrometeorology, cloud physics and atmospheric processes is an advantage.
• Demonstrated ability to work independently and as part of a team.
• Excellent oral and written communication skills in English.

To Apply: Interested candidates should send a CV with a list of at least 3 professional references and a cover letter explaining how your qualifications meet the posted requirements to veljko@umd.edu.

THE UNIVERSITY OF MARYLAND IS AN EQUAL OPPORTUNITY AFFIRMATIVE ACTION EMPLOYER