Technoculture Research is re-imagining how the world measures health by building micro-scale electrochemical laboratories that deliver lab-grade accuracy directly to clinicians, community health workers, and patients. Our platform combines microfabricated electrodes, advanced surface chemistries, and microfluidics to perform protein, nucleic-acid, and metabolite assays within minutes.
By replacing expensive optical detection methods with electron sensing technology, we aim to significantly reduce diagnostic costs and make precision healthcare accessible worldwide.
Job Description:
We are looking for a motivated Reinforcement Learning Intern to join our robotics team at SentientX (Sentient Industries Private Limited). The selected candidate will work on RL-based control policies with a focus on legged locomotion, including quadruped and humanoid robots, contributing to research and implementation efforts that bridge simulation and real-world deployment.
Selected intern's day-to-day responsibilities include
Train and evaluate reinforcement learning policies for robotic locomotion tasks in simulation environments.
Work with physics-based simulation environments to develop, test, and improve robot control behaviors.
Contribute to sim-to-real transfer research and implementation.
Implement and benchmark reinforcement learning algorithms such as PPO (Proximal Policy Optimization) and SAC (Soft Actor-Critic) for locomotion tasks.
Document experiments, results, and research findings clearly for the team.
Collaborate with the robotics engineering team on research and deployment projects.
Skill(s) required
Git Physics Python Reinforcement Learning Simulation and Modeling
Who can apply
Only those candidates can apply who
Don't want to miss the next one?
Subscribe to daily email alerts for roles matching your interests.
are available for full time (in-office) internship
can start the internship between 29th Jun'26 and 3rd Aug'26
are available for duration of 6 months
have relevant skills and interests
Other requirements
Requirements:
Strong understanding of Reinforcement Learning algorithms such as PPO, SAC, or equivalent methods.
Proficiency in Python and experience with RL frameworks like Stable-Baselines3, RLlib, or similar tools.
Familiarity with physics-based simulation environments, including MuJoCo, Isaac Gym, PyBullet, or related platforms.
Experience with Git and collaborative software development practices.
Background or coursework in robotics, control systems, or mechanical engineering is preferred.
Hands-on experience with locomotion policy training, quadruped/humanoid robots, URDF modeling, or ROS is an advantage.
Prior research or internship experience in robotics or machine learning labs is preferred.
Strong curiosity, self-motivation, and genuine interest in reinforcement learning and robotics.
Ability to work in a fast-paced research environment and collaborate effectively with teams.
Currently pursuing or recently graduated from a B.Tech, M.Tech, M.S., or Ph.D. program in Computer Science, Robotics, Electrical Engineering, or a related field.
Must demonstrate hands-on RL implementation through a GitHub repository, project, or assignment.
Strong understanding of PPO, SAC, sim-to-real transfer, domain randomization, system identification, and robust policy training.
Hands-on exposure to cutting-edge robotics and Physical AI research.
Number of openings
1
About Technoculture Research
Technoculture Research is reimagining how the world measures health by building micro-scale electrochemical laboratories that deliver lab-grade accuracy directly into the hands of clinicians, community health workers, and even patients at home. The platform integrates microfabricated electrodes, advanced surface chemistries, and microfluidics to enable rapid protein, nucleic-acid, and metabolite assays within minutes. By replacing expensive optical detection methods with electron sensing, the company significantly reduces both instrument and per-test costs- often by an order of magnitude- making precision diagnostics more accessible and scalable. With a clear mission to make diagnostics abundant, Technoculture Research aims to ensure that every critical health decision is supported by immediate, affordable, and reliable results, regardless of where care is delivered.
