Sessional Lecturer] Introduction to Reinforcement Learning – APS1080

Job title:

Sessional Lecturer] Introduction to Reinforcement Studying – APS1080

Firm

College of Toronto

Job description

Date Posted: 03/26/2024
Req ID: 36680
School/Division: School of Utilized Science & Engineering
Division: APSC: Ofc of the Dean – School Normal
Campus: St. George (Downtown Toronto)Description:Place: Sessional Lecturer I (1 positions obtainable)Course title and code: Introduction to Reinforcement Studying – APS1080Course description: Reinforcement Studying (RL) is a systems-level Synthetic Intelligence toolset; this course will present the scholar with each a stable theoretical basis and a powerful sensible understanding of the topic.RL permits autonomous brokers to deal with poorly-characterized, novel environments by exploring the setting to achieve information about it, and to use this data of the setting to behave in a goal-directed method. Though RL is positioned as one in every of three sides of Machine Studying, RL has far broader scope than the narrower instruments of supervised and unsupervised studying. RL, being based on agent design, has the objective of creating synthetic intelligence schemes that may endow an agent with autonomy. This introduction, thus, might be introduced inside the motivating context of an general AI system. There are three foundational RL instruments we are going to cowl (dynamic programming, Monte Carlo, Temporal-Distinction Studying); we will even present how hybridizations of those foundational instruments are employed to create manufacturing schemes. The scholar ought to go away the course with the flexibility to virtually apply this AI toolset to novel issues.Estimated Enrolment: Roughly 50 college studentsEstimated TA assist: TBAClass schedule: One 3-hour lecture per week.Sessional date of appointment: Summer time Could-August 2024Wage: Minimal stage of pay is $9,457.89 (Sessional Lecturer I), which incorporates trip pay, and should enhance relying on applicant’s stage of expertise and suitability for the place.{Qualifications}: PhD with a concentrate on AI or associated fields; expertise with Reinforcement Studying, Management Idea, Agent Design, and Synthetic Intelligence, in each a sensible and theoretical sense.Please word: Undergraduate or graduate college students and postdoctoral fellows of the College of Toronto are coated by the CUPE 3902 Unit 1 collective settlement relatively than the Unit 3 collective settlement, and shouldn’t apply for positions posted beneath the Unit 3 collective settlement.Temporary description of duties: Duties embody: preparation of lectures and course supplies; supply of lectures; attainable supervision of Instructing Assistants; setting and marking of initiatives, checks and exams; analysis of ultimate grades; contact with college students. On-line Supply.To point curiosity on this place, please full the CUPE UNIT 3 software type, downloaded from:and undergoWorkplace of the Vice Dean Graduate Research, School of Utilized Science and Engineering, College of Toronto44 St. George Road, Toronto, Ontario M5S 2E4, E mail:Closing Date: 04/07/2024, 11:59PM EDT
**This job is posted in accordance with the CUPE 3902 Unit 3 Collective Settlement.It’s understood that some bulletins of vacancies are tentative, pending last course determinations and enrolment. Ought to charges stipulated within the collective settlement fluctuate from charges acknowledged on this posting, the charges acknowledged within the collective settlement shall prevail.Choice in hiring is given to certified people superior to the rank of Sessional Lecturer II or Sessional Lecturer III in accordance with Article 14:12 of the CUPE 3902 Unit 3 collective settlement.Please word: Undergraduate or graduate college students and postdoctoral fellows of the College of Toronto are coated by the CUPE 3902 Unit 1 collective settlement relatively than the Unit 3 collective settlement, and shouldn’t apply for positions posted beneath the Unit 3 collective settlement.

Anticipated wage

Location

Toronto, ON

Job date

Wed, 27 Mar 2024 23:50:28 GMT

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