Applications that do not meet the expected qualifications below or do not follow the application instructions will not be considered.
There are several research and teaching assistantships available starting in Fall 2022 and Spring 2023, funded by NASA, SRC Inc, ESF and other sources. Experience in machine learning methods and strong programming skills are expected. While familiarity with remote sensing analysis is preferable, candidates with technical backgrounds from other fields and interest in geospatial applications are encouraged to apply.
– a master’s degree in engineering, computer science, physics, geography or related disciplines
– strong statistical and programming background
– experience with machine learning methods
– excellent English verbal and writing communication skills
– ability to collaborate and lead in a group environment
Experience with image analysis, deep learning methods and a relevant journal publication
The positions include an annual stipend, health insurance and a tuition waiver. They are based at SUNY ESF’s campus in Syracuse, NY, and the selected candidates are expected to be physically present. The positions are open to domestic and international students.
To apply please follow the instructions below carefully.
- Edit this attached document, responding specifically to the questions asked to the best of your ability. Your final response should not exceed 2 pages. The more specific you are to the information requested the better your chances. Convert your response to a pdf file. Applications that do not include this document completed will not be considered.
- Combine this two page pdf with your CV into a single pdf (place your CV after the two page info).
- Name this pdf file FirstName_Lastname_ESF.pdf, for example: Giorgos_Mountrakis_ESF.pdf
- Email this pdf to me at email@example.com
- Do NOT include any additional information, either as an attachment or inside the body of the email. If further information is needed I will reach out to you.
- Complete applications will receive a receipt email within three business days.
The positions are currently open, this page will be taken down when the positions are filled. So as long as you can read this, feel free to apply!
Related graduate programs
I accept students in the area of environmental monitoring and modeling with a focus on Remote Sensing, Machine Learning and Geographic Information Science. My research crosses several disciplines such as computer science, electrical engineering, environmental engineering, biology, ecology and forestry. There are three relevant graduate programs I am participating in:
Environmental Resource Engineering – Option Area: Geospatial Information Science and Engineering
Graduate Program in Environmental Science – Study Area: Climate and Energy
Graduate Program in Environmental Science – Study Area: Ecosystems: Land, Water and Air
The first program is more related to engineering, the second towards science. Both programs require strong quantitative skills. Please do not email me asking which program would be a better fit for you, only you can answer that question by checking the websites listed above.
Expected student knowledge and skills
Students from a wide range of backgrounds are encouraged to apply (engineering, geography, physics, math, biology, forestry). Furthermore, I only accept students with strong quantitative background since you will be joining an engineering department. If you do not like statistics for example this is not the right place for you. Minimum requirements include strong programming experience (e.g. Python, Matlab, R) and good communication skills (verbal, writing). Familiarity with GIS and Remote Sensing theory is preferable but not necessary as you can obtain that knowledge via coursework here.
Advising style and expectations
My job as your advisor is to motivate you to reach your full potential. That translates into hard work for both of us. You will be the major force for the research while I will find the time to advise you (within 1-2 days from your request) and make sure you have everything you need to succeed (e.g. computer hardware/software, attending conferences, etc). The University’s and the professor’s success comes from the student’s success, therefore it is to everyone’s interest to see you excel in your studies.
There is a clear expectation from both M.Sc. and Ph.D. students to produce high quality work published in related journals. Our M.Sc. students typically produce 1-2 journal publications and our Ph.D. students target 3-4 journal publications. PhD students usually have at least one manuscript published before defending their dissertation. Students are encouraged to submit their thesis in a manuscript format composed by an introduction, the papers and a summary section. This way papers are easily converted into thesis without too much additional work. There is no expected duration for your studies, motivated and productive students can graduate quickly assuming they meet the publication expectations.