Postdoctoral Fellow; Civil and Systems Engineering Faculty

The Postdoctoral Fellow will conduct research in decision-focused learning, an emerging paradigm that integrates predictive machine learning models directly with optimization to improve decision‑making under uncertainty. The primary research focus will be on developing novel end‑to‑end methodologies for addressing uncertainty in optimization constraints, particularly in scheduling and production planning applications where robust integrated solutions remain an open research challenge.

• Conduct independent and collaborative research in decision‑focused learning and optimization under uncertainty.
• Develop novel algorithms and computational methods that jointly learn predictive models and optimize decision‑making.
• Investigate methods for incorporating uncertainty in optimization constraints, with applications in scheduling, production planning, and related operational systems.
• Implement and evaluate proposed methods using computational experiments and real‑world datasets.
• Prepare manuscripts for publication in peer‑reviewed journals and present research findings at scientific conferences.
• Collaborate with faculty investigators and research team members on related research initiatives.
• Participate in grant proposal preparation and other research activities as assigned.

Doctoral degree in a related field.

Salary: $ 63,

The referenced salary range represents the minimum and maximum salaries for this position and is based on Johns Hopkins University's good faith belief at the time of posting. Not all candidates will be eligible for the upper end of the salary range. The actual compensation offered to the selected candidate may vary and will ultimately depend on multiple factors, which may include the successful candidate's geographic location, skills, work experience, internal equity, market conditions, education/training and other factors, as reasonably determined by the University.

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