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A Post-Doctoral Fellow (PDF) position in the Information and Computing Technologies Division at the College of Science and Engineering, Hamad Bin Khalifa University (HBKU) is open for hiring immediately in the areas of biomedical engineering, signal processing, big data, and machine learning. The successful candidate will work under the guidance of Dr. Marwa Qaraqe.
Position duties involve the publication of research results via journal and conference publications, conference presentations, interaction with academic institutions and industry, and grant proposal writing. The candidate will be also responsible for conducting research and mentoring MS and Ph.D. students in research projects. The candidate will also have the opportunity to develop his/her teaching experience.
It is important that the candidate present many of the following:
A Ph.D. or equivalent degree in Electrical Engineering or Biomedical Engineering.
Strong publication record in top academic conferences and journals.
Strong background in one or more of the areas listed above.
Strong simulation and programming skills.
Strong English writing and verbal skills.
Very good critical reasoning skills.
Very good knowledge of mathematical modeling and simulation.
Strong motivation with a desire to experiment and explore.
The ability to work both independently and collaboratively in teams.
HBKU offers a very competitive compensation package that includes an attractive salary and many generous benefits.
The location of the position is at Hamad Bin Khalifa University, Qatar Foundation, Doha, Qatar. The initial term of the PDF position is for 1 year, with possibility of renewal, based on mutual interest.
Candidates should send the following information, as .pdf or .doc attachments, to Dr. Marwa Qaraqe (email@example.com):
CV, including lists of publications, summary of educational background and grades
Summary of work experience
Short research statement (maximum 1 page)
Names and email addresses of at least 3 references.
A soft copy of one or two recent publications considered by the candidate as being representative(s) of his/her research work.