Careers

The role of the Science Communications Officer is to develop high-quality scientific and technical content that enhances understanding and knowledge dissemination.

The Science Communications Officer will conduct thorough research, write, edit and review papers, and work closely with colleagues to ensure accuracy and consistency. The Science Communications Officer will accurately translate complex scientific concepts into clear, concise and engaging content. They have a firm grasp of scientific terminology, excellent writing skills, and the ability to work under tight deadlines.

The Science Communications Officer will work closely with Michelle Simmons and other researchers and will report to the Chief Operating Officer.

Key responsibilities

+ Research scientific topics thoroughly and accurately.

+ Research, write, review and edit scientific articles, reports and papers.

+ Analyse and interpret complex scientific data and concepts, presenting it in a concise and engaging manner relevant for the target audience.

+ Collaborate with the Marketing and Communications Manager to ensure any technical content is accurately represented in marketing materials.

+ Collaborate with researchers and scientists to understand their findings ensuring accuracy and consistency, providing feedback to improve future papers/submissions.

+ Develop educational materials and tools that improve internal processes (particularly relating to scientific journal submissions).

+ Stay updated on latest research and scientific developments in relevant fields.

+ Stay updated on competitor papers and create regular reports on competitor achievements (particularly in scientific journals).

+ Ensure all scientific writing adheres to appropriate style, regulatory, and ethical guidelines.

+ Contribute to the creation and submission of research proposals and grant applications, working closely with the General Manager.

+ Liaise between authors, marketing and graphic designers to ensure the best visual communication of ideas in figures and other display items.

+ Manage multiple writing projects simultaneously, ensuring deadlines are met and stakeholders are kept up to date.

+ Excellent organisational and interpersonal skills.

+ Keen attention to detail.

+ The ability to bring creativity, innovation and energy to the team.

Qualifications

+ Master’s or Ph.D. degree in a relevant scientific field.

+ Proven experience as a skilled Science Communications Officer or similar role.

+ Strong knowledge of scientific terminology and principles.

+ Ability to absorb new areas of research and identify new developments in the quantum computing field.

+ Excellent writing, editing and proofreading skills.

+ Familiarity with scientific databases and research tools.

+ Proven ability to work under tight deadlines and prioritise tasks.

Pre-employment checks required for this position

+ Verification of qualifications.

+ Background checks.

+ Right to work check.

+ Join a world-class team at the cutting edge of technology, focussed on making quantum computers a reality

+ Collaborate with a diverse, multicultural team across the full stack quantum computer

An exciting opportunity exists for a PhD candidate to undertake a unique academic-industry program involving a collaboration between Silicon Quantum Computing Pty Ltd (SQC), the global leader in the manufacture and measurement of quantum processors engineered with atomic precision, UNSW Sydney, and CSIRO.

This prestigious Next Generation PhD scholarship stands out as it includes 11 weeks of funded coursework focusing on a holistic approach to problem-solving with technology. Diverse topics include deep learning, computer vision, ethics, decision making under uncertainty, innovation, and entrepreneurship.

Project Summary

Analogue quantum simulation is an emerging field for quantum chemistry, materials design, and for solving optimisation problems. The use of analogue rather than digital quantum systems allows for the direct mapping of high-valued computational problems onto near-term hardware that may offer an advantage over classical methods. Semiconductor quantum dots have recently been shown to exhibit the controllability and precision required to for analogue quantum simulation of complex physical systems such as magnetism and topological phases in condensed matter. At Silicon Quantum Computing (SQC), we are building a scalable platform for both digital and analogue quantum computation. The digital architecture relies on the spins of single electrons and phosphorus nuclei embedded in a silicon crystal. However, the analogue approach focuses on the use of quantum dots formed using the same phosphorus donors in silicon to directly simulate “atoms” in one- and two-dimensional lattices. Using these quantum processors, we can embed computationally difficult problems to be used as a feature generator for machine learning.

This project will focus on the design, theoretical understanding and measurement of analogue quantum feature generators for quantum-enhanced machine learning. The analogue processors will be fabricated with sub-nanometre precision using a UHV scanning tunnelling microscopy hydrogen-lithography combined with phosphine dosing. The fabricated processors will then be measured in a He³ dilution refrigerator operating at a few mK using various electrical measurement techniques. The successful student will be privy to the entire fabrication and measurement process and can work with internal/external collaborators in condensed matter and quantum chemistry problems. Depending on the processor different analysis/control techniques may be developed including machine learning, feedback controls, and radio-frequency measurement techniques.

This position reports to Dr Sam Gorman and works alongside the full stack team (staff and students) funded by SQC.

Candidate experience

Candidates for this project should have a background in quantum computing, machine learning, or condensed matter physics. Experience and knowledge of the theory of machine learning and/or statistics is highly desirable. General research experience and knowledge of cryogenic systems are also highly desirable with a significant component of the PhD focused on measurements of cryogenic systems.

About SQC

+ SQC is an Australian research and development company, with the specific aim of building a quantum computer based on atom qubits in silicon.

+ SQC is a well-funded Australian company formed by the Commonwealth Government, the New South Wales State Government, Commonwealth Bank of Australia, Telstra, and UNSW Sydney.

+ SQC is seeking to commercialise silicon quantum computing technology developed in Australia – technology that has the potential to have a global impact.

+ SQC’s work is building on more than 20 years of world-leading research by the Centre of Excellence which includes the development of dedicated manufacturing and measurement techniques for an atom-based quantum computer in silicon.

+ This role and SQC are located at SQC on the UNSW Sydney campus.

Eligibility

To be eligible for a scholarship, applicants must be domestic students as per the Higher Education Support Act at the time of award. Domestic students include:

+ Australian citizens

+ Australian permanent residents

+ a person entitled to stay in Australia, or to enter and stay in Australia, without any limitation as to time

+ a New Zealand citizen.

As determined by the Faculty Higher Degree Committee (HDC), the minimum requirement for admission to a PhD at UNSW is:

+ a Bachelor degree with first or upper second-class Honours, or

+ a completed Master by Research with a substantial research component and demonstrated capacity for timely completion of a high-quality research thesis.

The PhD application process is available here: https://www.unsw.edu.au/research/hdr/application

Key Requirements

+ Students must register and complete the coursework component of the Next Generation Graduates Program within the first 18 months of receipt of a scholarship.

+ Students who receive a scholarship are expected to undertake their training in Australia and endeavour to remain in Australia for two years following completion of their degree.

Remuneration

+ Stipend rate (p.a.): $41,650

+ Training (p.a.): $5,000

+ Travel (total): $5,000

+ Thesis allowance (total): $840

If this role is for you, send your CV to careers@sqc.com.au

+ Join a world-class team at the cutting edge of technology, focussed on making quantum computers a reality

+ Collaborate with a diverse, multicultural team across the full stack quantum computer

An exciting opportunity exists for a PhD candidate to undertake a unique academic-industry program involving a collaboration between Silicon Quantum Computing Pty Ltd (SQC), the global leader in the manufacture and measurement of quantum processors engineered with atomic precision, UNSW Sydney, and CSIRO.

This prestigious Next Generation PhD scholarship stands out as it includes 11 weeks of funded coursework focusing on a holistic approach to problem-solving with technology. Diverse topics include deep learning, computer vision, ethics, decision making under uncertainty, innovation, and entrepreneurship.

Project Summary

This research project will explore quantum algorithms for solving quantum chemistry and condensed matter problems using SQC’s atom qubits in silicon quantum computing platform. The research will focus on both near-term applications on Noisy Intermediate-Scale Quantum (NISQ) devices and long-term feasibility studies of fault-tolerant quantum computing for large-scale quantum chemistry and condensed matter simulations. The work will involve implementing and optimizing quantum algorithms, analyzing their performance on real quantum hardware, and determining the ultimate resources required for fault-tolerant scalability.

A key aspect of this project is the development of NISQ algorithms such as the Variational Quantum Eigensolver (VQE) and small-scale Quantum Phase Estimation (QPE) approaches for small-scale quantum chemistry and condensed matter problems. The implementation will take into account the specific constraints of phosphorus-in-silicon architectures, such as gate fidelities and qubit connectivity. Error mitigation strategies will also be explored to improve accuracy and reliability in practical computations.

In addition to studying NISQ applications, this project will investigate how quantum chemistry and condensed matter problems can be mapped onto large-scale, fault-tolerant quantum computers. This includes analyzing the requirements for logical qubits, quantum gate operations, and execution times within the framework of quantum error correction (QEC). The specific mapping to QEC schemes, such as the surface code, will be evaluated in the context of phosphorus-in-silicon platforms to determine their efficiency and feasibility, and how such algorithms can be optimised for the silicon platform.

The research will also involve benchmarking quantum chemistry and condensed matter calculations on currently available silicon quantum hardware and longer-term fault tolerant platforms and the challenges there. Simulation tools will be developed to predict algorithm performance on both NISQ and fault-tolerant devices, providing insights into the potential advantages of quantum computing for solving and condensed matter problems. The project aims to lay the groundwork for executing and optimizing quantum chemistry and condensed matter algorithms on phosphorus-in-silicon quantum processors, facilitating the transition from NISQ to large-scale fault-tolerant quantum computation.

This position reports to Associate Professor Charles Hill and works alongside the full stack team (staff and students) funded by SQC.

Candidate experience

Candidates for this project should have a background in quantum computing, computational chemistry, or condensed matter physics. Experience with quantum programming frameworks such as Qiskit, or Cirq, as well as classical computational chemistry software like PySCF, would be beneficial. Familiarity with quantum error correction and the constraints of silicon-based qubits is advantageous but not required. This research will contribute to the practical realization of quantum computational chemistry and condensed matter on scalable quantum architectures, leveraging the unique advantages of phosphorus-in-silicon qubits.

About SQC

+ SQC is an Australian research and development company, with the specific aim of building a quantum computer based on atom qubits in silicon.

+ SQC is a well-funded Australian company formed by the Commonwealth Government, the New South Wales State Government, Commonwealth Bank of Australia, Telstra, and UNSW Sydney.

+ SQC is seeking to commercialise silicon quantum computing technology developed in Australia – technology that has the potential to have a global impact.

+ SQC’s work is building on more than 20 years of world-leading research by the Centre of Excellence which includes the development of dedicated manufacturing and measurement techniques for an atom-based quantum computer in silicon.

+ This role and SQC are located at SQC on the UNSW Sydney campus.

Eligibility

To be eligible for a scholarship, applicants must be domestic students as per the Higher Education Support Act at the time of award. Domestic students include:

1. Australian citizens,
2. Australian permanent residents,
3. a person entitled to stay in Australia, or to enter and stay in Australia, without any limitation as to time; or
4. a New Zealand citizen.

As determined by the Faculty Higher Degree Committee (HDC), the minimum requirement for admission to a PhD at UNSW is:

1. a Bachelor degree with first or upper second-class Honours, or
2. a completed Master by Research with a substantial research component and demonstrated capacity for timely completion of a high-quality research thesis.

The PhD application process is available here: https://www.unsw.edu.au/research/hdr/application

Key Requirements

+ Students must register and complete the coursework component of the Next Generation Graduates Program within the first 18 months of receipt of a scholarship.

+ Students who receive a scholarship are expected to undertake their training in Australia and endeavour to remain in Australia for two years following completion of their degree.

Remuneration

+ Stipend rate (p.a.): $41,650

+ Training (p.a.): $5,000

+ Travel (total): $5,000

+ Thesis allowance (total): $840

If this role is for you, send your CV to careers@sqc.com.au

Position Summary

An exciting opportunity exists for an experienced technician with a background in electronics. This role, Hardware Technician, uses previously acquired skills to build, install and maintain high performance instrumentation in cryogenic laboratories housing quantum computing devices.

The role would involve working with world-leading atomic electronics and quantum computing teams at SQC based at UNSW Sydney.  This role will support the development of a large-scale digital quantum computer based on atom-qubits in silicon as the team works to scale to an error-corrected architecture.

The person in this role would be responsible for deploying and maintaining quantum device control instrumentation and wiring across SQC’s cryogenic laboratories and installations. The role will work with world-leading quantum physicists and hardware/software engineers to support existing infrastructure and to deploy new instrumentation that delivers increased measurement capabilities.

The Hardware Technician reports to the Hardware Engineering Lead and works closely with the hardware and measurement teams. The position will have no direct reports.

Responsibilities

+ Construction, testing, installation/commissioning and documentation of control system instrumentation interfacing with cryogenic systems.

+ Construction, testing and commissioning of cryogenic wiring, PCBs and devices in dilution fridges and cryostats.

+ Troubleshooting and solving technical problems with custom equipment and installations.

+ Creating bug reports and supporting the debugging process by attempting to recreate issues in the room temperature laboratory.

+ Undertake inventory management of laboratory stocks including organising equipment calibration and repairs.

+ Printed circuit board assembly and rework.

+ Cooperate with all health & safety policies and procedures of SQC.

Selection Criteria

+ Relevant tertiary qualification with subsequent relevant experience or equivalent competence gained through any combination of education, training and experience.

+ Minimum three years’ experience.

+ Demonstrated experience in electronic assembly, testing and commissioning.

+ Ability to read and follow mechanical drawings and wiring diagrams.

+ Demonstrated knowledge and experience in the troubleshooting of IT based integrated systems and electronic equipment.

+ Ability to utilise laboratory workshop tools and test equipment, to repair and assemble electronic and cryogenic systems

+ Excellent written and verbal communication skills.

+ A high level of attention to detail to build high-quality assemblies and products.

+ Demonstrated RF experience including use of spectrum analysers, network analysers and oscilloscopes (desirable).

+ Knowledge of health & safety responsibilities and commitment to attending relevant health and safety training.

Pre-employment checks required for this position

+ Verification of qualifications

+ Background checks

We look forward to receiving your application. Please include a cover letter addressing the selection criteria.

If this role is for you, send your CV to careers@sqc.com.au

+ Join a world-class team at the cutting edge of technology, focussed on making quantum computers a reality

+ Collaborate with a diverse, multicultural team across the full stack quantum computer

+ Enjoy the sunny shores and stunning scenery of Sydney, Australia

We are seeking a highly skilled Senior Machine Learning Specialist who can build the right model for the right job. This role requires a strong background in understanding use-case requirements, developing tailored machine learning models, and delivering outcome-driven solutions.

Position Summary

The Senior Machine Learning Specialist works with world-leading atomic electronics and quantum computing teams at SQC based at UNSW Sydney.

This role designs and develops machine learning models to support classification and inference tasks that use a quantum computer in real client use-cases. The Specialist will work with ML experts both internally and client organisations to develop and implement the best models for decisioning across finance, networking, and more.

The Specialist works alongside quantum physicists, hardware engineers, and software engineers to translate business requirements into technical solutions that will harness SQC’s globally unique quantum computer processors, thus adding value to end-users’ existing ML workflows.

This position reports to the Head of Software Engineering and works alongside other staff and students funded and employed by SQC. While this role does not have any direct reports, it is expected that they will assist where necessary with the supervision of other team members.

About SQC

+ Silicon Quantum Computing (SQC) is one of the most prominent companies in the quantum computing industry globally. Our aim is to build the world’s first, full-scale quantum computer to help solve complex challenges beyond the abilities of classical computers.

+ SQC is a well-funded Australian company formed by the Commonwealth Government, the New South Wales State Government, Commonwealth Bank of Australia, Telstra, and UNSW Sydney.

+ SQC is seeking to commercialise silicon quantum computing technology developed in Australia – technology that has the potential to have a global impact.

+ SQC’s work is building on 20+ years of world-leading research by the Centre of Excellence which includes the development of dedicated manufacturing and measurement techniques for an atom-based quantum computer in silicon.

+ This position is based in Sydney, at our SQC offices in Kensington, with occasional travel required.

+ We foster a collaborative and inclusive environment where innovation and continuous learning are encouraged. Join us in leveraging cutting-edge quantum machine learning techniques to drive transformative changes across diverse industries.

+ SQC is dedicated to building a diverse workforce and an inclusive work environment. We welcome applications from all qualified individuals, regardless of background.

Opportunities and Accountabilities 

+ Drive the development and implementation of machine learning models from inception to deployment, focusing on solving complex problems.

+ Collaborate closely with internal and end user ML experts across various domains, helping to integrate our ML models with theirs and/or advising them on how to improve their approach.

+ Define clear problem statements and translate business requirements into technical solutions.

+ Utilise advanced machine learning techniques and algorithms to extract insights and drive decision-making processes.

+ Work closely with quantum physicists and researchers to identify, quantify and execute unique ML solutions using our quantum systems.

+ Evaluate and recommend tools, technologies, and frameworks that enhance the efficiency and effectiveness of machine learning projects.

+ Stay updated with the latest advancements in machine learning and related fields, applying new methodologies to improve model performance and scalability.

About the successful applicant

To be successful in this role you will have:

+ Deep expertise with the various capabilities available when tailoring a model, e.g.:

+ Learning paradigms (supervised, unsupervised, reinforcement)

+ Problem types (classification, regression, generative)

+ Architectures (linear models, trees, neural networks, ensembles)

+ Purposes (predictive, descriptive, prescriptive)

+ Hyperparameters (learning rate, epoch counts, depth)

+ Other optimization techniques (feature engineering, regularization, tuning)

+ Performance evaluation (recall, RMSE, learning curves, benchmarking)

+ Bachelor’s degree, Master’s degree, or PhD in Computer Science, Engineering, Statistics, or a related quantitative field.

+ Proven track record of successfully developing and deploying machine learning models in real-world applications, with demonstrable impact on business outcomes.

+ Expertise in problem statement definition, experimental design, model selection, and evaluation metrics.

+ Hands-on experience with machine learning libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and proficiency in programming languages such as Python, Scala and/or R.

+ Five or more years’ experience in a senior machine learning role.

+ Experience with big data technologies and cloud platforms (e.g., AWS, Azure, Google Cloud).

+ Familiarity with data engineering practices and data pipeline development.

If this role is for you, send your CV to careers@sqc.com.au

+ Join a world-class team at the cutting edge of technology, focussed on making quantum computers a reality

+ Collaborate with a diverse, multicultural team across the full stack quantum computer

+ Enjoy the sunny shores and stunning scenery of Sydney, Australia

An exciting opportunity exists for an Atomic Fabrication Scientist to undertake a unique academic-industry position in a start-up company, Silicon Quantum Computing Pty Ltd (SQC), co-located with the Australian Research Council Centre of Excellence for Quantum Computation and Communication (CQC²T or the Centre), based at UNSW Sydney. This position will be in one of Australia’s leading research teams conducting world-leading research in atomic electronics and quantum computing with the specific aim of building a quantum computer based on atom-qubits in silicon. Silicon Quantum Computing is an Australian research and development company, working hard to make quantum computers a reality.

Position Summary

The Atomic Fabrication Scientist optimises the fabrication of nanometre to atomic scale devices in silicon. This includes the ongoing development of unique semiconductor fabrication techniques and processes and the operation of an ultra-high vacuum scanning tunnelling microscopy / molecular beam epitaxy (STM/MBE) system for the production of atomic-scale devices for studies of coherent transport of quantum information in multi-qubit architectures.

The Atomic Fabrication Scientist works alongside atomic-scale device fabrication scientists, clean-room managers, and device processing engineers to fabricate atomic-scale silicon devices with controlled dopant profiles and support the overall fabrication of globally unique quantum computer processors.

This position reports to the Senior Research Fellow, Dr Joris Keizer, and works alongside other staff and students funded by SQC as well as CQC2T. While this role does not have any direct reports, it is expected that they will assist where necessary with the supervision of other team members.

About SQC

+ SQC is an Australian research and development company, with the specific aim of building a quantum computer based on atom qubits in silicon.

+ SQC is a well-funded Australian company formed by the Commonwealth Government, the New South Wales State Government, Commonwealth Bank of Australia, Telstra, and UNSW Sydney.

+ SQC is seeking to commercialise silicon quantum computing technology developed in Australia – technology that has the potential to have a global impact.

+ SQC’s work is building on more than 20 years of world-leading research by the Centre of Excellence which includes the development of dedicated manufacturing and measurement techniques for an atom-based quantum computer in silicon.

+ This role and SQC are located at the headquarters of the Centre at UNSW Sydney.

Opportunities and Accountabilities 

+ Responsible for the reproducible execution of a globally unique atomic-scale device fabrication process of excellent quality.

+ Drive the reproducible execution of device fabrication processes on a day-to-day basis.

+ Responsible for the ongoing development of the atomic-scale device fabrication process for improved device metrics and high yield.

+ Design, fabrication and measurement of atomic-scale silicon qubit devices.

+ Conduct the operation and maintenance of ScientaOmicron Nanotechnology variable and low-temperature scanning probe microscopes and MBE systems.

+ Design, fabricate and measure internationally unique atomic-scale, multi-qubit devices in silicon using scanning probe lithography and molecular beam epitaxy (MBE).

+ Undertake detailed analysis of individual process steps for optimisation and improvement and provide thorough reports.

+ Work closely with clean-room managers and device processing engineers to further the electrical interface and chip layout of multi qubit devices.

+ Provide technical assistance and training to the research staff and students working on the current process.

+ Liaise with the Senior Research Fellow and team to ensure efficient delivery of atomic-scale devices.

+ Start developing independent research experiments/projects for troubleshooting processing issues and improving the yield and efficiency of atomic-scale device fabrication process.

+ Implement safety systems including OH&S, hazardous substances, risk assessments and conformance with AS’s codes.

+ Assist with the training and guidance of atomic fabrication and cleanroom engineers and scientists.

+ Align with and actively demonstrate the UNSW Values in Action: Our Behaviours and the UNSW Code of Conduct.

+ Cooperate with all health and safety policies and procedures of the university and take all reasonable care to ensure that your actions or omissions do not impact on the health and safety of yourself or others.

About the successful applicant

+ A PhD in Physics, Materials Science, Engineering, and/or relevant field.

+ Demonstrated work experience in a research environment including hands-on experience of scanning tunnelling microscopy.

+ Proven commitment to proactively keeping up to date with discipline knowledge and developments.

+ Demonstrated ability to conduct independent research.

+ Demonstrated strong track record in research with outcomes of high quality and high impact with clear evidence of the desire and ability to continually achieve research excellence as well as the capacity for research leadership.

+ Demonstrated internationally recognised work in ultra-high vacuum scanning probe microscopy or molecular beam epitaxy.

+ Demonstrated experience in one of the following areas is required:

– STM of semiconductor surfaces, preferably silicon;

– high resolution STM-lithography;

– crystal growth by MBE;

– single atom manipulation;

– spin measurements by STM; or

– spectroscopy measurements by STM

+ Experience in fabrication and research of nanostructured and mesoscopic devices on semiconductor materials, such as silicon, III-V semiconductors.

+ Experience in troubleshooting and solving complex fabrication issues.

+ Experience of working in close knit teams to optimise complex semiconductor device processes.

+ Well-organised, attention to detail and ability to meet deadlines.

+ Demonstrated ability to work in a multidisciplinary team, collaborate across disciplines and build effective relationships.

+ An understanding of and commitment to UNSW’s aims, objectives and values in action, together with relevant policies and guidelines.

+ Knowledge of health and safety responsibilities and commitment to attending relevant health and safety training.

If this role is for you, send your CV to careers@sqc.com.au

+ Join a world-class team at the cutting edge of technology, focussed on making quantum computers a reality

+ Collaborate with a diverse, multicultural team across the full stack quantum computer

+ Enjoy the sunny shores and stunning scenery of Sydney, Australia

The Quantum Machine Learning Scientist works within a truly multi-disciplinary team of scientists and engineers at the forefront of atomic electronics and quantum computing internationally, funded by Silicon Quantum Computing Pty Limited (SQC) and based at UNSW Sydney.

Position Summary

This role will work closely with hardware, software and processing engineers to realise quantum processors in silicon ensuring high-fidelity control and measurement of multi-qubit devices at cryogenic temperatures. The Quantum Machine Learning Scientist will develop different machine learning protocols, including reservoir computing, extreme learning machines and kernel methods, for near-term implementations of both analogue and digital quantum computers. They will use SQC’s analogue quantum devices, comprised of large arrays of phosphorus-doped silicon quantum dots, as a computational resource to solve certain well-defined computational tasks to demonstrate potential advantage over classical computational methods. Additionally, this role will develop machine learning models for digital quantum computers focusing on protocols that can be implemented with a 100-qubit silicon-based quantum processor, as the broader SQC team works to scale quantum devices from 10-qubit to 100-qubit architectures within the next 5 years. Where necessary, this role will assist with the support and supervision of PhD and undergraduate students and other members of the Algorithms and Architectures team members.

The Quantum Machine Learning Scientist will report to Dr Casey Myers, the Algorithms and Applications team lead, and also work closely with Associate Professor Charles Hill, the Quantum Architectures team lead, alongside other staff and students funded by SQC.

About SQC

+ SQC is an Australian research and development company, with the specific aim of building a quantum computer based on atom qubits in silicon.

+ SQC is a well-funded Australian company formed by the Commonwealth Government, the New South Wales State Government, Commonwealth Bank of Australia, Telstra, and UNSW Sydney.

+ SQC is seeking to commercialise silicon quantum computing technology developed in Australia – technology that has the potential to have a global impact.

+ SQC’s work is building on more than 20 years of world-leading research by the Centre of Excellence which includes the development of dedicated manufacturing and measurement techniques for an atom-based quantum computer in silicon.

+ This role and SQC are located at the headquarters of the Centre at UNSW Sydney.

Opportunities and Accountabilities 

Level A: 

+ Develop quantum machine learning models with near-term quantum systems.

+ Design and implement machine learning protocols with analogue quantum systems using near-term arrays of phosphorus-doped silicon quantum dots.

+ Design and implement machine learning protocols with digital quantum algorithms on near-term, atom-based silicon hardware.

+ Adapt, tailor, and develop quantum machine learning protocols for industry focussed applications.

+ Work on the theory of quantum machine learning to determine when/how a quantum advantage can be achieved for both analogue and digital quantum computing.

+ Work with a multidisciplinary team of quantum physicists, engineers, technicians, postdoctoral researchers, and PhD students for early-stage quantum system implementations on silicon-based quantum computer devices.

+ Generate high quality research publication output.

+ Provide technical assistance and training to the research staff and students working within SQC.

+ Align with and actively demonstrate the UNSW Values in Action: Our Behaviours and the UNSW Code of Conduct.

+ Cooperate with all health and safety policies and procedures of the university and take all reasonable care to ensure that your actions or omissions do not impact on the health and safety of yourself or others.

Level B: (in addition to the above)

+ Make significant contribution to the field of quantum machine learning.

+ Where appropriate, take leadership of research projects.

+ Supervise honours or other higher degree research students

About the successful applicant

To be successful in this role you will have:

Level A:            

+ A PhD in Physics, Computer Science, Mathematics, or relevant field, with work experience in a research or commercial environment.

+ Demonstrated experience in classical machine learning techniques, with expertise in reservoir computing, extreme learning machines or kernel methods.

+ Demonstrated research capabilities in quantum machine learning or a related field.

+ Experience writing high-performance quantum algorithm implementation, preferably in Python, MATLAB, C/C++, or equivalent. GPU programming and/or high-performance computing experience.

+ Experience with Python quantum computing packages such as OpenQASM (Qiskit), Cirq, Project Q, or equivalent.

+ Experience in troubleshooting and solving complex unplanned issues.

+ Well-organised, attention to detail and ability to meet deadlines.

+ High level written and verbal communication skills and the ability to network effectively and interact with a diverse range of students and staff.

+ Demonstrated ability to work in a team, collaborate across disciplines and build effective relationships.

+ An understanding of and commitment to UNSW’s aims, objectives and values in action, together with relevant policies and guidelines.

+ Knowledge of health and safety responsibilities and commitment to attending relevant health and safety training.

Level B: (in addition to the above)

+ Demonstrated ability to conduct independent research in machine learning or quantum algorithms with a track record in research with outcomes of high quality and high impact with clear evidence of the desire and ability to continually achieve research excellence as well as the capacity for research leadership.

+ Demonstrated significant experience in classical machine learning techniques, with expertise in reservoir computing, extreme learning machines or kernel methods.

+ Demonstrated outstanding research capabilities in quantum machine learning or a related field.

+ Experience solving problems with machine learning on quantum systems.

+ Experience modelling qubit systems.

+ Significant experience with Python quantum computing packages, such as OpenQASM (Qiskit), Cirq, ProjectQ, or equivalent.

+ Experience with co-supervision of higher degree research students in quantum computing.

If this role is for you, send your CV to careers@sqc.com.au

Who we are

Silicon Quantum Computing Pty Limited (SQC) is at the forefront of global efforts to build a commercial-scale quantum computer and bring quantum computing to market. Established in May 2017, it is the world’s first atomic precision manufacturing company focused on delivering the highest quality qubits and commercial outcomes as they scale. SQC has significant backing from Telstra, the Commonwealth Bank of Australia, UNSW Sydney, and the Australian Federal and New South Wales governments. With AU$283m in funding to date and a highly integrated team of engineers, SQC has developed a full-stack quantum computer in-house and is capable of rapid iteration and product deployment at speed.

About the role

This position will be in one of Australia’s leading research teams conducting world-leading research in atomic electronics and quantum computing with the specific aim of building a quantum computer based on atom-qubits in silicon. Silicon Quantum Computing is an Australian research and development company, working hard to make quantum computers a reality.

The Associate Quantum Engineer supports the development of quantum processors based on precision-placed atom qubits in silicon. In particular, the Associate Quantum Engineer designs, tests, characterises, and optimises multi-qubit devices based on nuclear spin qubits and electron spin qubits, develops control schemes for fast magnetic control of individual spins, the controlled coupling between them, and the processing of quantum information.

This position reports to the Quantum Engineering Lead, Dr Ludwik Kranz. While this role does not have any direct reports, it is expected that they will assist where necessary with the support of other students and team members.

Key responsibilities

+ Develop and perform low noise, high frequency measurements of multi-qubit devices in silicon.

+ Assist in setting up, optimising, and operating experimental setups based on cryogenic dilution refrigerator.

+ Conduct experiments, gather, compile, prepare, and analyse data.

+ Write and analyse the code for execution and analysis of the measurements.

+ Undertake analysis of project data for publication including the preparation of manuscripts.

+ Where appropriate, assume leadership of projects.

+ Regularly report on progress regarding findings back to the team.

+ Assist the design, fabrication, and optimisation of atomic-scale silicon qubit processors.

+ Work with a multidisciplinary team of quantum physicists, engineers, technicians, postdoctoral researchers and PhD students to establish optimal setting for rapid development of atomic-scale silicon quantum processors.

+ Assist the operation and maintenance of laboratory and specialised electronic equipment (high frequency signal generators, DACs and ADCs, oscilloscopes etc.).

+ Cooperate with all health and safety policies and procedures and take all reasonable care to ensure that your actions or omissions do not impact on the health and safety of yourself or others.

Essential Experience

+ Master’s degree in physics, electrical engineering and/or experimental physics or equivalent and experience in measuring multi-qubit devices in either a commercial or academic environment.

+ Demonstrated experience using common RF and microwave test equipment (e.g., signal generators, spectrum analysers, network analysers, oscilloscopes).

+ Demonstrated ability to conduct independent research.

+ Proficiency in a range of programming languages (e.g. Python).

+ Excellent IT skills, including experience with word processing such as MS-WORD, LaTex or equivalent.

+ Excellent verbal and written communication skills and the ability to liaise effectively with all stakeholders.

+ Well-organised, attention to detail and ability to meet deadlines.

+ Demonstrated ability to think logically, create solutions and make informed decisions.

+ Ability and willingness to work in a team where credit is shared.

+ Proactive and positive mindset when confronting challenges.

+ Knowledge of health and safety responsibilities and commitment to attending relevant health and safety training.

Differentiating Experience

+ Demonstrated experience in high frequency (GHz) measurement techniques and microwave engineering.

+ Demonstrated experience performing Electron Spin Resonance (ESR) or Nuclear Magnetic Resonance (NMR) experiments.

+ Demonstrated experience setting up or running a cryogenic dilution refrigerator.

+ An excellent research track record in the discipline area as evidenced by conference presentations and publications.

+ Demonstrated research in quantum computing.

+ Experience in fabricating nanoscale devices.

Pre-employment checks required for this role

+ Verification of qualifications

+ Background checks

If this role is for you, send your CV to careers@sqc.com.au