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ICTP seeks applications for a postdoctoral fellow position starting Fall 2022 from outstanding early-career computational scientists of any nationality with a strong interest and demonstrated experience in the application of Machine Learning, Artificial Intelligence or data science methods to any of the fields of interest of ICTP (physics, mathematics, chemistry, life and earth sciences and related disciplines). Experience in HPC technology and programming in massively parallel environments is highly desirable.
Fellows will conduct research activity in their own field of research and provide guidance and support in applied ML, AI or data science methods to ICTP scientists and visitors. The fellow will also contribute to the ICTP training activities in these fields.
The position is associated with the soon-to-be-announced International Consortium on Scientific Computing, a new ICTP initiative aimed at creating a common platform for the global community in the field of scientific computing.
The ICTP takes seriously its commitment to equal opportunity and diversity in hiring, and in its global mission to promote science in the developing world.
Fellows must have completed a PhD prior to the start of their fellowship and preferably have a previous postdoctoral or equivalent professional experience.
ICTP offers internationally competitive remuneration and a number of benefits, including a pension contribution and special allowances for family members. The take-home base salary ranges from 2,100 to 2,700 Euro monthly, depending on experience, in addition to family and pension benefits. The initial appointment will be made for two or three years, with the possibility of renewal for up to a total of four years. Candidates should apply using the ICTP online application system. They are required to arrange for the submission of three letters of recommendation by established researchers. Incomplete applications will not be considered.
Application deadline: 30 September 2022
Apply online at https://e-applications.ictp.it/applicant/login/3805
