Research Associate (Limited Term)
University of Toronto
Toronto, ON
The Advanced Thermal/Fluids Optimization, Modelling and Simulation (ATOMS) Laboratory, founded in 2007 by Cristina H. Amon, Dean of the Faculty of Applied Science & Engineering and Alumni Professor in Mechanical & Industrial Engineering, is looking to fill a Research Associate position. ATOMS research methods involve numerical simulations of multi-scale systems using in-house and commercial codes. Our current research aims to advance the understanding of: (i) fluid and transport phenomena in biological and energy systems, (ii) transport phenomena in energy applications and electrical vehicles, and (iii) optimization of complex systems.

The Research Associate will work under the supervision of Dr. Amon to coordinate research, training and outreach activities in the ATOMS Lab, interact with industrial and academic partners, prepare reports and presentations for industrial partners, develop research proposals and funding applications, supervise and train undergraduate/graduate students on a day-to-day basis, author scientific publications and conference talks, and provide general technical and scientific guidance to ATOMS lab personnel. In addition, the Research Associate will coordinate and delegate administrative tasks in support of the lab’s mission.

  • Doctoral (Ph.D., Sc.D.) degree in Mechanical Engineering, Physics or related fields with a focus on modeling and simulation of transport phenomena and simulation-based optimization.
  • Minimum of ten (10) years of experience in an academic setting, working directly in the supervision of undergraduate/graduate students, teaching undergraduate/graduate courses, and/or directing research projects.
  • Academic experience of at least three (3) years, as graduate student, postdoctoral fellow or academician in Canada.
  • Due to the broad research vision and ongoing projects of the ATOMS Laboratory, the applicant should have demonstrated experience working in projects that deal with both Renewable and Non-Renewable Energy Sources (e.g. Hydrocarbons, Aeolian, Geothermal etc.), Transport, Multi-objective Optimization and Metamodeling.
  • Knowledge of and experience with optimization methods, such as Genetic Algorithms, Simulated Annealing, MCMC and Direct Signal Analysis (damped least-squares method) applied to complex systems
  • Knowledge of and experience with metamodeling methods applied to problems of transport phenomena, namely neural networks, neurofuzzy algorithms, kriging, support-vector regression and fractal theory
  • Knowledge of and experience in neural networks, fuzzy logic, Bayesian statistical tools and/or discriminant and cluster analyses, applied to pattern-recognition problems
  • Experience in financial management of environmental projects, to incorporate costs of net generated renewable energy to optimization algorithms
  • Familiarity with multi-phase fluid flow in porous media, such as in simulation and characterization of oil reservoirs
  • Familiarity with the Geophysical approaches to the study of stratified anisotropic media, in order to model friction between the air and ground surface in terrains with topographic roughness (boundary-layers)
  • Strong technical and analytical skills with solid understanding of research methodologies, with outstanding record of peer-reviewed ISI publications
  • Excellent communication skills, both written and oral
  • Good programming practical experience in Matlab and/or Phyton
  • Proficient in Microsoft Office suite (Word, Excel, PowerPoint), and scientific visualization software (e.g. Matlab).
  • Ability to identify opportunities for research and collaboration with Canadian industries
  • Well-developed interpersonal, communication and analytical skills
  • Ability to mentor effectively students and to exercise tact and judgement in working with personnel under their supervision
  • Demonstrated initiative and technical ability
  • Detail-oriented
  • Ability to work independently, with minimal supervision
Travel: None

Notes: This is a limited term (2 Years), renewable

All qualified candidates are encouraged to apply; however, Canadians and permanent residents will be given priority.