... reinforcement learning, robotics and computer vision. Considerations: Exceptions to standard rates may apply to courses with unique credit hours, supervision, labs, clinical/practicum courses ...
... reinforcement learning, robotics and computer vision. Considerations: Exceptions to standard rates may apply to courses with unique credit hours, supervision, labs, clinical/practicum courses ...
... reinforcement learning, robotics and computer vision. Considerations: Exceptions to standard rates may apply to courses with unique credit hours, supervision, labs, clinical/practicum courses ...
... reinforcement learning, robotics and computer vision. Considerations: Exceptions to standard rates may apply to courses with unique credit hours, supervision, labs, clinical/practicum courses ...
... and robotics. RPL develops the open-source Modular Autonomous Discovery for Science (MADSci ... Generative models, reinforcement learning, and agent-based approaches to streamline experimentation ...
... and robotics. RPL develops the open-source Modular Autonomous Discovery for Science (MADSci ... Generative models, reinforcement learning, and agent-based approaches to streamline experimentation ...
... and robotics. RPL develops the open-source Modular Autonomous Discovery for Science (MADSci ... Generative models, reinforcement learning, and agent-based approaches to streamline experimentation ...
... and robotics. RPL develops the open-source Modular Autonomous Discovery for Science (MADSci ... Generative models, reinforcement learning, and agent-based approaches to streamline experimentation ...
AV Simulation Domain Expert (Sr. Principal) - US (Remote) or Chicago, IL
Chicago, IL · On-site +1
$170K - $250K/yr
Background in reinforcement learning, end-to-end driving systems, or multi-agent simulation. * Experience in automotive, robotics, or other safety-critical domains, including familiarity with ISO ...
AV Simulation Domain Expert (Sr. Principal) - US (Remote) or Chicago, IL
Chicago, IL · On-site +1
$170K - $250K/yr
Background in reinforcement learning, end-to-end driving systems, or multi-agent simulation. * Experience in automotive, robotics, or other safety-critical domains, including familiarity with ISO ...
Postdoctoral Appointee - Materials Informatics and Autonomous Synthesis
Lemont, IL · On-site
$72K - $121K/yr
... reinforcement learning for experiments, or uncertainty quantification * Experience with autonomous, self-driving, or robotic laboratory platforms * Background in electronic polymers, conjugated ...
Postdoctoral Appointee - Materials Informatics and Autonomous Synthesis
Lemont, IL · On-site
$72K - $121K/yr
... reinforcement learning for experiments, or uncertainty quantification * Experience with autonomous, self-driving, or robotic laboratory platforms * Background in electronic polymers, conjugated ...
... reinforcement learning for experiments, or uncertainty quantification * Experience with autonomous, self-driving, or robotic laboratory platforms * Background in electronic polymers, conjugated ...
... reinforcement learning for experiments, or uncertainty quantification * Experience with autonomous, self-driving, or robotic laboratory platforms * Background in electronic polymers, conjugated ...
Assistant Scientist - AI for Autonomous Synthesis and Multimodal Characterization
Lemont, IL · On-site
Laboratory automation and robotic synthesis platforms * Generative models, reinforcement learning, or agentic AI approaches for materials discovery and experiment planning * Multimodal data fusion ...
Assistant Scientist - AI for Autonomous Synthesis and Multimodal Characterization
Lemont, IL · On-site
Laboratory automation and robotic synthesis platforms * Generative models, reinforcement learning, or agentic AI approaches for materials discovery and experiment planning * Multimodal data fusion ...
Reinforcement Learning Robotics information
What are some common challenges faced when implementing reinforcement learning algorithms in robotics projects?
One common challenge in this role is bridging the gap between simulation and real-world environments, as algorithms that perform well in simulation may not translate directly to physical robots due to unpredictable variables and hardware limitations. Additionally, ensuring the safety and stability of the robot during training is crucial, since trial-and-error learning can sometimes result in unintended behaviors or hardware damage. Collaboration with hardware engineers and domain experts is often necessary to fine-tune models, interpret results, and iterate on solutions. Overcoming these challenges requires patience, adaptability, and strong communication skills within a multidisciplinary team.
What are the key skills and qualifications needed to thrive as a Reinforcement Learning Robotics Engineer, and why are they important?
To thrive as a Reinforcement Learning Robotics Engineer, you need a strong background in robotics, machine learning, and programming, typically supported by a degree in computer science, engineering, or a related field. Expertise with frameworks like TensorFlow or PyTorch, experience with simulation environments (such as Gazebo or ROS), and familiarity with reinforcement learning algorithms are essential. Strong problem-solving skills, creativity, and effective communication set standout professionals apart in this rapidly evolving field. These skills enable engineers to develop intelligent robotic systems that adapt and learn efficiently, driving innovation and practical deployment in real-world environments.
What is reinforcement learning in robotics?
Reinforcement learning in robotics refers to a type of machine learning where robots learn to perform tasks through trial and error, receiving feedback from their actions in the form of rewards or penalties. This approach allows robots to autonomously develop complex behaviors by interacting with their environment, rather than relying solely on pre-programmed instructions. Reinforcement learning is especially useful for tasks that are difficult to model explicitly, such as walking, grasping, or navigation. Over time, the robot improves its performance by maximizing the cumulative reward, leading to more efficient and adaptive behaviors.
What is the difference between Reinforcement Learning Robotics vs Machine Learning Engineer?
| Aspect | Reinforcement Learning Robotics | Machine Learning Engineer |
|---|---|---|
| Required Credentials | Degree in Robotics, Computer Science, or related fields; knowledge of reinforcement learning | Degree in Computer Science, Data Science, or related fields; expertise in machine learning algorithms |
| Work Environment | Robotics labs, manufacturing, autonomous systems | Tech companies, data-driven projects, software development |
| Industry Usage | Autonomous robots, industrial automation, research | Data analysis, predictive modeling, AI applications |
Reinforcement Learning Robotics focuses on applying reinforcement learning techniques to control and optimize robotic systems, often in physical environments. Machine Learning Engineers develop algorithms for a broad range of applications, including data analysis and predictive modeling. While both roles require knowledge of machine learning, Reinforcement Learning Robotics emphasizes robotics and real-world interaction, whereas Machine Learning Engineers work across various industries with software-based solutions.
What are popular job titles related to Reinforcement Learning Robotics jobs in Chicago, IL? For Reinforcement Learning Robotics jobs in Chicago, IL, the most frequently searched job titles are:
What job categories do people searching Reinforcement Learning Robotics jobs in Chicago, IL look for? The top searched job categories for Reinforcement Learning Robotics jobs in Chicago, IL are:
What cities near Chicago, IL are hiring for Reinforcement Learning Robotics jobs? Cities near Chicago, IL with the most Reinforcement Learning Robotics job openings:
Full-time, Part-time
Re-posted 7 days ago
DePaul University rating
7.2
Based on 29 frontline employees who took The Breakroom Quiz
345th of 555 rated colleges and universities
Job description
Description
DePaul's Jarvis College of Computing & Digital Media (CDM) is located in the heart of Chicago's Loop, the central business district of Chicago. Our students represent many different experiences, perspectives, and cultures, and the university strives to recruit and sustain a faculty community where all backgrounds are valued and supported. Part-time teaching positions are available throughout the academic year, including summer sessions. Academic course schedules fluctuate from quarter to quarter, and the college will work with selected individuals to determine a quarterly schedule. Courses are not guaranteed, however the college does its best to give ample notice about available courses. Applicants with expertise that matches course scheduling needs will be contacted for an interview.
The School of Computing (SoC) offers a variety of undergraduate and graduate programs including Computer Science, Artificial Intelligence, Cybersecurity, Data Science, Game Programming, Health Informatics, Human-Computer Interaction, Information Systems, Information Technology, Intelligent Systems Engineering, Network Engineering and Security, and Software Engineering. Find out more about SoC at https://www.cdm.depaul.edu/academics/Pages/School-of-Computing.aspx.
Qualifications
Minimum requirements include a master's degree in the discipline, or 18 semester/27 quarter hours of graduate work in the discipline, or an undergraduate degree with a minimum of five years demonstrated relevant professional experience. Exceptions may be considered with approval of the dean.
Application Instructions
The School of Computing offers a MS in Artificial Intelligence degree. At the end of the degree, students will be able to design and implement complex intelligent systems and integrate AI techniques into existing applications and processes. Students take courses in core AI concepts and techniques and explore relevant technical areas including natural language processing, big data systems, computer vision, image processing, robotics, and cybersecurity. We seek instructors with professional experience in machine learning and artificial intelligence who can teach in areas relevant to AI including machine learning, deep learning, natural language processing, reinforcement learning, robotics and computer vision.
Considerations:
Exceptions to standard rates may apply to courses with unique credit hours, supervision, labs, clinical/practicum courses, coaching, administrative tasks, and courses that are either over-enrolled or under-enrolled.
General Compensation/Benefits Statement:
DePaul University has provided a compensation range that represents its good faith estimate of what the University may pay for the position at the time of posting. The salary offered to the selected candidate will be determined based on factors such as (but not limited to) the qualifications, education, experience, and training of the selected candidate, the scope and responsibilities of the position, departmental budget availability, internal salary equity considerations, and available market information.
DePaul University offers a variety of benefit options for qualified part-time employees. Further information regarding benefits can be found here: https://offices.depaul.edu/human-resources/benefits/part-time/Pages/default.aspx
About DePaul University's Academic Calendar:
Except for the College of Law, DePaul University operates on a quarter system. Classes in Autumn, Winter, and Spring quarters are 11 weeks in length (including finals week) and Summer courses, in two sessions, are typically 5 weeks in length. The College of Law operates on the semester system. Classes in the Fall and Spring semesters are 16 weeks in length (including finals week) and it offers a Summer Session of 7 weeks (including final exams).
DePaul's Jarvis College of Computing & Digital Media (CDM) is located in the heart of Chicago's Loop, the central business district of Chicago. Our students represent many different experiences, perspectives, and cultures, and the university strives to recruit and sustain a faculty community where all backgrounds are valued and supported. Part-time teaching positions are available throughout the academic year, including summer sessions. Academic course schedules fluctuate from quarter to quarter, and the college will work with selected individuals to determine a quarterly schedule. Courses are not guaranteed, however the college does its best to give ample notice about available courses. Applicants with expertise that matches course scheduling needs will be contacted for an interview.
The School of Computing (SoC) offers a variety of undergraduate and graduate programs including Computer Science, Artificial Intelligence, Cybersecurity, Data Science, Game Programming, Health Informatics, Human-Computer Interaction, Information Systems, Information Technology, Intelligent Systems Engineering, Network Engineering and Security, and Software Engineering. Find out more about SoC at https://www.cdm.depaul.edu/academics/Pages/School-of-Computing.aspx.
Qualifications
Minimum requirements include a master's degree in the discipline, or 18 semester/27 quarter hours of graduate work in the discipline, or an undergraduate degree with a minimum of five years demonstrated relevant professional experience. Exceptions may be considered with approval of the dean.
Application Instructions
The School of Computing offers a MS in Artificial Intelligence degree. At the end of the degree, students will be able to design and implement complex intelligent systems and integrate AI techniques into existing applications and processes. Students take courses in core AI concepts and techniques and explore relevant technical areas including natural language processing, big data systems, computer vision, image processing, robotics, and cybersecurity. We seek instructors with professional experience in machine learning and artificial intelligence who can teach in areas relevant to AI including machine learning, deep learning, natural language processing, reinforcement learning, robotics and computer vision.
Considerations:
Exceptions to standard rates may apply to courses with unique credit hours, supervision, labs, clinical/practicum courses, coaching, administrative tasks, and courses that are either over-enrolled or under-enrolled.
General Compensation/Benefits Statement:
DePaul University has provided a compensation range that represents its good faith estimate of what the University may pay for the position at the time of posting. The salary offered to the selected candidate will be determined based on factors such as (but not limited to) the qualifications, education, experience, and training of the selected candidate, the scope and responsibilities of the position, departmental budget availability, internal salary equity considerations, and available market information.
DePaul University offers a variety of benefit options for qualified part-time employees. Further information regarding benefits can be found here: https://offices.depaul.edu/human-resources/benefits/part-time/Pages/default.aspx
About DePaul University's Academic Calendar:
Except for the College of Law, DePaul University operates on a quarter system. Classes in Autumn, Winter, and Spring quarters are 11 weeks in length (including finals week) and Summer courses, in two sessions, are typically 5 weeks in length. The College of Law operates on the semester system. Classes in the Fall and Spring semesters are 16 weeks in length (including finals week) and it offers a Summer Session of 7 weeks (including final exams).
What DePaul University employees say
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Benefits
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About DePaul University
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Industry
Colleges, universities, and professional schools
Company size
1,001 - 5,000 Employees
Headquarters location
Chicago, IL, US
Year founded
1898