Post-doctoral fellow in modeling of of bioaerosols, layer-clouds and climate with AI (PA2023/2802)

Updated: about 1 month ago
Job Type: FullTime
Deadline: 25 Oct 2023

Subject description
Climate modelling is within the general field of geobiosphere science and is an aspect of physical geography and ecosystem science.

Bioaerosols in mixed-phase clouds can initiate ice and thereby may influence the precipitation and microphysical properties of the clouds, such as the numbers and sizes of cloud-particles aloft. This in turn may influence radiative fluxes and meteorological conditions at the land surface where the bioaerosols are emitted. It is an open question whether bioaerosols, if their microphysical effects are treated in detail with competing sources of ice also represented, can influence the climate on the global scale.

Mixed-phase layer-clouds (‘stratiform’ clouds) may be essential for such a linkage, if it exists.  Although active bioaerosols are far less numerous than other types of aerosol particles that initiate ice in most of the troposphere above the freezing level, they can be more numerous at warm subzero temperatures (e.g. warmer than about -10 degC).  Thus, stratiform layer-clouds entirely at such warm subzero levels might be expected to be more influenced by biological ice nucleation than other cloud-types. 

The project will research this topic by quantifying the linkage between bioaerosols, layer-clouds and climate. A postdoctoral fellow-position for two years is to be filled. 

Work duties
The main duties involved in a post-doctoral posistion is to conduct research. Teaching may also be included, but up to no more than 20% of working hours. The position shall include the opportunity for three weeks of training in higher education teaching and learning.

These tasks will be performed:

  • Improve treatment of fragmentation in ice-ice collisions by analysis of video imagery from observations outdoors;
  • Simulate a case of layer-cloud observed in USA, comparing with coincident observations;
  • Predict the impact from various groups of bioaerosols on the simulated cloud properties;
  • Treat the linkage between bioaerosols and clouds on the global scale with a deep learning tool.

This will involve coding with FORTRAN 90 and python languages in a linux environment.  The work will be mostly performed in a team of atmospheric modellers at the Department of Physical Geography and Ecosystem Science.

Qualification requirements
Appointment to a post-doctoral position requires that the applicant has a PhD, or an international degree deemed equivalent to a PhD, within the subject of the position, completed no more than three years before the date of employment decision. Under special circumstances, the doctoral degree can have been completed earlier.

Additional requirements:
Researchers with a background in numerical modeling and knowledge of mesoscale meteorology are encouraged to apply. 

 Applicants must have:

  • PhD degree in meteorology or equivalent
  • BSc in physics or equivalent
  • Oral and written proficiency in English.
  • Programming language experience in a linux environments, with the Fortran and python languages
  • Experience with graphics packages (e.g. matlab).

Assessment criteria and other qualifications
This is a career development position primarily focused on research. The position is intended as an initial step in a career, and the assessment of the applicants will primarily be based on their research qualifications and potential as researchers.

Particular emphasis will be placed on research skills within the subject.

For appointments to a post-doctoral position, the following shall form the assessment criteria:

  • A good ability to develop and conduct high quality research.
  • Teaching skills.

Additional criteria:
Documented knowledge, preferably from his / her university education in:

  • mathematics, especially differential equations;
  • numerical methods and computer programming; and
  • physical meteorology, especially cloud microphysics, including the initiation and growth of ice particles.

Experience with artificial intelligence software would be an advantage.

Consideration will also be given to good collaborative skills, drive and independence, and how the applicant’s experience and skills complement and strengthen ongoing research within the department, and how they stand to contribute to its future development.

Terms of employment
This is a full-time, fixed-term employment of 2 years. The period of employment is determined in accordance with the agreement “Avtal om tidsbegränsad anställning som postdoktor” (“Agreement on fixed-term employment as a post-doctoral fellow”) between Lund University, SACO-S and OFR/S, dated 1st February 2022.

The position will start on 15 February 2024 or at a mutually agreed date and last for two years. At the end of the two years, the results should be summarized in a written report.

Enquiries about the position can be made to Vaughan Phillips (vaughan.phillips@nateko.lu.se).

Instructions on how to apply
Applications shall be written in English and be compiled into a PDF-file containing:

  • résumé/CV, including a list of publications,
  • a general description of past research and future research interests (no more than three pages),
  • contact information of at least two references,
  • copy of the doctoral degree certificate, and other certificates/grades that you wish to be considered.

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