{"id":3411475,"url":"https://alion.io/job/kaust-discovery-computational-scientist","title":"Computational Scientist","company":{"id":36398,"name":"KAUST","domain":"kaust.edu.sa","url":"https://alion.io/company/kaust-discovery","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":null},"role":"Science & Research","role_family":"Science & Research","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Saudi Arabia"],"countries":["SA"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":33000,"max_usd":74000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":1296},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"C++","optional":false},{"name":"CUDA","optional":false},{"name":"Fortran","optional":false},{"name":"HPC","optional":false},{"name":"Machine Learning","optional":false},{"name":"MPI","optional":false},{"name":"OpenMP","optional":false},{"name":"Python","optional":false},{"name":"C","optional":true}],"status":"live","first_seen_at":"2026-09-02T00:00:00Z","employer_posted_date":"2026-09-02","last_verified_at":"2026-10-31T05:07:18Z","board_verified":true,"closed_at":null,"days_open":59,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":59},"description":"Position Summary\nThe position consists in providing a broad range of support and training for users of laboratory systems and their\nsoftware applications. In addition to user support through our ticketing system, the candidate is expected to\nprovide advanced support in computational science and engineering, big data analysis, machine learning, or any\nrelated field.\nSenior candidate should initiate and autonomously work on scientific and/or operational impact project(s) in\ncollaboration with KAUST faculty member or with teams in the lab or other core labs, in the framework of\nmethod development projects impacting a wide range of research groups by proposing new added-value\nservices within the lab.\nMajor Responsibilities\nSupport enablement activities for research work in computational science and engineering\nand data analysis including but not limited to:\nProvide timely and useful user support via telephone, walk-in, email, and ticketing system\nsubmissions for all types of inquiries with ability to handle advanced level support.\nMaintain high customer service standards in dealing with and responding to user issues and\nquestions.\nInstallation, porting and tuning of parallel applications, tools and data analysis software stack.\nMaintain scientific, technical and professional currency through collaboration, practice,\ntraining, conferences, independent learning, and other means.\nMaintain a broad knowledge of state-of-the-art computer technology, equipment, and\nsystems and support benchmarking activities in the lab for future procurements.\nReview and prepare documentation for systems, tests and installation of software\nProvides individual and/or group instruction and training on topics of interest to the user\ncommunity. Become the reference on campus in a topic of expertise.\nDevelop software tools and parallel application libraries as necessary to support the research\nprojects in the cluster systems and subsystems.\nDevelop software application benchmarks for periodic upgrades of laboratory systems.\nArticulate and pursue research activities aligned with the laboratory and with personal\nstrengths and interests; pursue co-authorship of papers/presentations as appropriate; engage\nin scientific communication and outreach.\nAny additional duties as required for the operation of the lab and assigned by the line\nmanagers.\nSenior candidates (L5) are also expected to:\nContribute and take charge of major tasks in lab leadership projects, such as the refresh of\nShaheen Supercomputer, as assigned by Lead and Lab Director.\nInitiate collaborative projects and activities with other groups within the lab, and across other\ncore labs when applicable.\nIncrease national and international visibility of KAUST and Core Labs through active\nparticipation and representation of the lab in relevant events.\nCompetencies\nExpertise in using or supporting computational science and engineering, data analysis, and\nartificial intelligence applications and libraries in different HPC environments.\nDemonstrated ability to support research activities in an HPC environment\nDemonstrated ability to work successfully in a highly collaborative research environment\nProficiency in programming HPC applications and tools (e.g. Fortran, C/C++, Python, MPI,\nOpenMP, CUDA, OpenACC, etc.).\nExcellent analytical, problem solving and decision-making skills\nCreative and innovative individual with clear initiatives to improve lab operation\nFlexible and delivers high-quality results within deadlines\nPlanning and organizational skills\nAbility to work in teams, influence peers and achieve results.\nThe ability to handle multiple projects simultaneously\nAbility to work effectively in multi-cultural environment\nDemonstrated ability to prepare written and to give oral reports in English\nStrong verbal and written communication skills in English.\nSenior candidates (L5) are also expected to have the following competencies:\nTrack record of publications and other contributions in computational science and engineering\nand data analysis venues.\nBecome the reference scientist of commonly used concepts, practices, and procedures within\nthe related field of expertise.\nStrong team player with a track record of initiative and responsiveness.\nOrganizational understanding and global thinking.\nMastering project management principles and practices.\nThe ability to handle multiple projects simultaneously with autonomy.\nQualifications & Experience\nPh.D. in computer science, computational science and engineering or any closely related discipline.\nA demonstrated relevant experience of minimum 4 year after PhD is required.\nSenior candidates (L5) are expected to have a minimum of 8 years 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