Job Opportunities Within Our Group

We are looking to recruit two AI/ML doctoral students to join our group.

Credit: By Viktor Forgacs on Unsplash.

Feb 7, 2023. Our research group is inviting applications for doctoral researchers in AI/ML. We seek talented candidates with strong analytical and implementation skills and eager to engage in one or more of the following topics: (i) temporal point process and probabilistic modeling based on them, (ii) deep learning approaches to signal characterization, representation and processing and (iii) causal reasoning/inference in the context of deep learning. Both positions will be available starting in the summer of 2023. Admittance decisions will be made on a rolling basis, until the positions are filled.

More About The Positions

The candidates are expected to contribute to the state-of-the-art of foundational AI/ML and impact with their work other disciplines, such as the Earth Sciences. By the graduation time, they are expected to have a strong publication record in high-tier journals/venues and have become independent researchers with significant expertise in their respective areas. On the other hand, the candidates can expect strong research/career mentoring and immersion into a conducive research environment with strong emphasis on collaborative and interdisciplinary work, as well as the oppotunity to work with a network of highly respected scholars and researchers.

The candidates will be fully supported financially (full tuition scholarship & competitive stipends) through their active involvement in one of the following interdisciplinary projects:

  • Seismic Event DiscriminationDeLAEINE is a joint effort with the private sector to significantly enhance our ability to discriminate between natural and man-made seismic events based on their seismic traces. Approaches towards this entail deep learning and feature engineering informed by the physics of seismic wave propagation as sensed by multiple seismological stations.

  • Flash flood nowcasting in West Africa from Satellite Imagery – Selected for funding in 2023 by NASA under its SERVIR program, this mulit-institutional effort aims to develop an ensemble flash flood nowcasting system based on satellite observations and weather forecasts to deliver timely predictions that will facilitate effective preparation and response to imminent flooding threats in West Africa. Within this context, our group will contribute a number of deep learning based precipitation nowcasting approaches.

A prerequisite for employment is the candidate(s) being admitted to one of the following doctoral programs at FIT: Electrical Engineering, Computer Engineering, Computer Sciences or Applied Mathematics. Please consult FIT’s program-specific application requirements for these doctoral programs.

Finally, please note that

  • unlike other public Florida or US universities, FIT does not have country-specific admission requirements.
  • our team is firmly committed to diversity and inclusion.


  • The candidates should have a strong engineering and/or discrete mathematics background and a pronounced affinity to rigorous analytical work. A solid background in signal processing is highly desirable. Furthermore, they should have strong implementation skills and, in particular, should be compentent programmers in Python. Prior experience with ML frameworks, such as PyTorch and TensorFlow, is also desirable.

  • In order to be admitted to a doctoral program, FIT requires applicants to have earned a minimum GPA of 3.0 (on a scale of 4.0) in undergraduate work, if applying to the doctoral program after the completion of their bachelor’s degree, or a minimum GPA of 3.2 (on a scale of 4.0) in prior graduate coursework, if applying to the doctoral program after the completion of their master’s degree.

  • Candidates must be proficient in both the oral and written use of English. International candidates, which are not exempt from English language requirements, must provide documentation of their proficiency according to FIT’s language requirements.

How To Apply

Before applying to any of the aforementioned doctoral programs, please email the group’s lead, Dr. Georgios C. Anagnostopoulos ( the following artifacts in PDF format:

  • Transcripts (unofficial are acceptable) in English.
  • A current CV/resume.
  • A statement of objectives

Regarding the CV/resume, please ensure to include (i) any past research experience, (ii) any publications you may have contributed to and a very brief description of your contribution(s), (iii) if available, references to samples of scientific software that you have contributed to (could be a link to a GitHub repository) and (iv) the names and contact information of at least two professional references that are familiar with you, your academic work and accomplishments. Also, limit your statements of objectives to one page, state your professional/scholarly goals succintly and briefly argue why you may be a good candidate for one of these positions.

Please direct all your inquiries about this opportunity to Dr. Anagnostopoulos. To stay in touch with our group and become aware of future opportunities with our group, follow him on Twitter and/or on LinkedIn.

Georgios C. Anagnostopoulos
Georgios C. Anagnostopoulos
Associate Professor of Electrical & Computer Engineering

I lead the Machine Learning Research Group at FIT.