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Faraz Esfahani

Data Analysist (Mechanical Engineer)

Can work in or around Toronto

  • 43.64877
  • -79.38171
  • Rate On-demand
  • Experience 0-2 years
Propose a project The project will begin once you accept Faraz's quote.

This freelancer is available part-time (Evenings & weekends) but hasn't confirmed their availability in over 7 days.

Part-time, Evenings & weekends

Propose a project The project will begin once you accept Faraz's quote.

Location and workplace preferences

Location
Toronto, ON, Canada
Can work onsite in your office in
  • around Toronto and 50km

Preferences

Project length
  • ≤ 1 week
  • ≤ 1 month
Business sector
  • Mechanical Engineering
  • Medical
  • Pharmaceuticals industry
Company size
  • 1 person
  • 2-10 people
  • 11 - 49 people
  • 50 - 249 people
  • 250 - 999 people
+2 autres

Verifications

Freelancer code of conduct signed
Read the Malt code of conduct

Verified email

Languages

  • Persian

    Native or bilingual

  • English

    Fluent

Categories

Skills (12)

Faraz in a few words

My name is Faraz. I'm a mechanical engineer working on drug discovery as my master's thesis. I'm studying super-resolution algorithms using CNNs and GANs for resolution enhancement. Also classification algorithms for drug discovery purposes.

Experience

York University

Graduate Research And Teaching Assistant

Toronto, ON, Canada

September 2021 - Today (9 months)

Teaching Assistant :
• Fluid dynamics
• Renaissance Engineer 2: Engineering Design Principles
• Thermofluid Laboratory

Ferdowsi University of Mashhad

Undergraduate Research Assistant

Mashhad, Razavi Khorasan Province, Iran

January 2016 - September 2019 (3 years and 8 months)

Established laboratory instrumentation to study steam generation performance of different samples and zinc oxide (ZnO) nanoparticles in solar vapour generation. Supported two research projects by conducting experiments, extracting raw data, analyzing data, and drawing conclusions. Successfully completed both research studies yielding concrete results leading to two publications.
• ZnO on mulberry wood (ZnO-wood) improved evaporation efficiency by 17% and 39% compared to ZnO nanofluid and water.
• Increased the evaporative efficiency from 47% to 58% in the superficial approach and from 37% to 40% in the volumetric approach.
• Completed cost analysis illustrating ZnO-Wood nanoparticles are more cost-effective compared to other nanoparticles.

Education