IFHE Hyderabad

Schemes of Service: Research Division: Engineering Employment Type: Fixed Term As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to develop industry-relevant applied research skillsets while working on translational robotics and AI projects. The primary responsibility of this role is to support a joint SIT–DSO research project focused on evaluating and developing humanoid robot capabilities for door opening and doorway traversal in human-centric environments. The Research Engineer will contribute to humanoid robot system integration, teleoperation-based data collection, simulation-based synthetic data generation using NVIDIA Isaac Sim, and learning-based policy development for manipulation and locomotion tasks. The role will involve both experimental robotics work and AI model development for sim-to-real humanoid manipulation research. Key Responsibilities Participate in and manage the research project together with the Principal Investigator (PI), Co-PI, and research team members to ensure project deliverables are achieved. Undertake the following responsibilities in the project: i. Humanoid Robot System Integration Configure and integrate humanoid robot hardware and software systems for door opening and doorway traversal tasks. Support calibration, perception, locomotion, manipulation, and control pipeline integration. ii. Experimental Testbed Development Design and set up representative door interaction experimental environments. Conduct baseline testing and benchmarking for humanoid manipulation and traversal tasks. iii. Teleoperation and Data Collection Develop and operate teleoperation pipelines for humanoid robot data collection. Collect, process, and manage robot demonstration datasets including perception, robot states, and control data. iv. Simulation and Synthetic Data Generation Develop simulation environments and synthetic data generation workflows using NVIDIA Isaac Sim and Omniverse technologies. Implement domain randomization and scenario variation pipelines for robust sim-to-real learning. v. AI Model Development Support development and evaluation of learning-based control policies using reinforcement learning, imitation learning, and visuomotor learning approaches. Assist in model training, testing, benchmarking, and deployment on real robotic platforms. vi. Research and Technical Reporting Conduct literature reviews and experimental studies related to humanoid robotics and sim-to-real learning. Prepare technical reports, publications, and presentation materials for project reviews and dissemination. Carry out Risk Assessment and ensure compliance with Workplace Safety and Health regulations. Coordinate procurement and liaison with vendors/suppliers. Work independently and within a multidisciplinary team to ensure proper operation and maintenance of robotics equipment and experimental infrastructure. Assist in co-supervision of Final Year Project (FYP) or capstone students together with the project PI. To communicate and liaise with internal and external stakeholders to ensure project deliverables are met. Any other ad-hoc duties assigned by Supervisors. Key Requirements Bachelor’s, Master’s, or PhD degree in Robotics, Mechanical Engineering, Electrical Engineering, Computer Science, or related fields. Experience in robotics software development using ROS/ROS2. Experience with robotic simulation platforms such as NVIDIA Isaac Sim, Isaac Lab, Gazebo, or MuJoCo. Familiarity with humanoid robots, robotic manipulators, or locomotion systems. Knowledge of machine learning, reinforcement learning, imitation learning, or computer vision techniques for robotics applications. Strong analytical and problem-solving skills. Good written and verbal communication skills. Ability to work independently and collaboratively in multidisciplinary teams. The following will be advantageous: Experience with teleoperation systems and data collection pipelines. Experience with NVIDIA Omniverse or sim-to-real workflows. Experience with reinforcement learning frameworks or visuomotor policy training. Experience working with dexterous hands or humanoid manipulation platforms. Key Competencies Strong interest in robotics and embodied AI research. Able to build and maintain strong working relationships with internal and external stakeholders. Self-directed learner with strong initiative and ownership of work. Strong analytical and critical thinking skills. Proficient in technical writing and presentation. Able to work effectively in experimental and rapidly evolving research environments.

Salary: £24,521 - £26,093 per annum Contractual hours: 37 Basis: Full Time Package: Full details can be found here - https://www.ucb.ac.uk/about-us/work-for-us/rewards-and-benefits/ Job category/type: Finance, Professional Services Job reference: REQ000560 Attachments: attachmentFinance Admin Asst - JDPS - June 2026.pdf University College Birmingham is seeking a highly organised individual to join the Finance Team. As a key member of the team, you will be the first point of contact to deal with general finance queries and provide support to the Finance Assistants and wider Finance Team. The successful candidate will demonstrate: Relevant Admin experience Organisation skills High level of IT skill Accuracy and attention to detail Ability to work on own initiative and part of a team  If you are looking to work in a fast-paced, financial environment this is the role for you. Standard Information UCB is an equal opportunities employer. University College Birmingham is proud to be TEF rated Silver, with a Good Ofsted rating UCB has achieved the Investors in Diversity Bronze Award. You may need to obtain permission to work in the UK if you don’t already have the unrestricted right to work in any role. There are various types of visa which include the right to work. You can check if you need a UK visa using the Government’s online tool and find information about UK visa routes and the eligibility criteria that must be met for each route Work in the UK - GOV.UK (www.gov.uk). All staff are required to prove their right to work in the UK before they start work. All applicants for employment at the University will be expected to undertake an Enhanced Check with the Disclosure and Barring Service prior to commencement. All applicants for employment at the University will be expected to demonstrate an understanding of the principles of Safeguarding and the PREVENT agenda in the context of further and higher education.

At the heart of SIT’s mission is to nurture industry-ready graduates equipped with deep technical expertise and transferable skills to tackle tomorrow’s challenges. SIT collaborates with industry in our education, while benefitting them with our talent supply and collaborative research achievements. The University’s unique applied learning pedagogy integrates work and study, embedding authentic learning experiences within real-world environments. Through strategic partnerships forged by our faculty with industry, learners bridge theoretical knowledge with practical application in and out of the classroom. Such active & authentic learning opportunities ensures graduates step into their careers with applicable skills and competence. In research, SIT faculty aims to bridge knowledge creation and utilisation. Our faculty collaborates closely with industry on translational research and innovation with focus on addressing pertinent industry challenges to impact businesses. The Singapore Teaching and Academic Research Talent (START) Scheme is co-funded by the Ministry of Education (MOE) and SIT to encourage and support outstanding young Singaporeans interested in pursuing an academic career at SIT. The Applied Research Fellowship aims to provide doctoral candidates who are about to complete or have recently completed their studies an opportunity to engage in advanced training and/or research at an overseas university for one year. Besides financial support, awardees will also receive academic mentorship. Upon completion of the Fellowship, awardees will be considered for Assistant Professorship. Eligibility and Selection Criteria Singapore citizen  Doctoral candidates who have recently completed or are about to complete their studies in a discipline under the supported areas for START below Excellent academic record plus a high degree of proficiency and motivation for selected research area Have been accepted or have applied for a postdoctoral training at a leading overseas university in a research area that is aligned with SIT’s supported areas A keen interest in an academic career Value of Fellowship The Fellowship provides: Monthly stipend Overseas maintenance allowance Return economy airfare Conference and fieldwork grants Overseas medical insurance Fellows will also each be assigned a SIT faculty mentor throughout their post-doctoral training and have opportunities to participate in faculty development programmes. The fellowship is tenable for one year. On an exception basis, a two-year programme may be supported. Service Commitment One year for every year of sponsorship. Application Process Applications are open throughout the year via the various links below. Applications received before 15 January 2026 will be considered for the 2026 intake.  Interview by the respective clusters for shortlisted applicants will be conducted throughout the year. Final Interview by the Panel for shortlisted applicants for the 2026 intake will commence in Mid-March to End April 2026. Awards will be finalised by July 2026. Supported Areas for START - Food, Chemical and Biotechnology Sustainable and Functional food: Sustainable food systems and circular food economy - alternative proteins, upcycled ingredients); AI and automation in food manufacturing - smart sensors, digital twins, and AI-driven food quality control and processing; Food safety - supply chain tracking/monitoring, blockchain Biotechnology: Host strain screening and engineering for microbial bioprocess development; microbial physiology and adaptation for industrial applications; high-throughput screening and automation for strain optimization; bioprospecting for novel microbial hosts, enzymes, and metabolites to support sustainable biomanufacturing. (Bio)pharmaceuticals: Processing science and technology for bio- and chemical transformations, separations, purifications and formulation applied to pharmaceuticals manufacture; modelling of processing steps and whole processes to support innovation, design, optimisation and control for manufacturing operations. Process control: process modelling, control, and optimization, with applications in chemical and pharmaceutical manufacturing; data-driven modelling and machine learning applications in process industries; advanced process control (APC); model predictive control (MPC); digital twins and real-time process monitoring and control; process analytical technology (PAT); process intensification and sustainability.