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JOIN OUR EFFORTS TO

BUILD A UNIVERSAL COMPUTING PARADIGM

THROUGH VENTURE.

For decades hardware developers have raced against each other to accelerate computing by shrinking transistor size and increasing processor density but we are quickly approaching a fundamental limit. New architectures are emerging as an alternative to capitalise on task parallelism and optimised hardware layouts for a small class of functions such as those used in machine learning. Alongside this, completely novel systems (neuromorphic, photonic, quantum) are being developed independently without a way to interoperate with each other and existing architectures.

However, this processor-centric model used ubiquitously for the past 75 years is fundamentally incompatible with the current data-driven landscape due to the outdated view of information and storage. The software developed for these rigid systems is completely inflexible requiring an entire team of software developers working years to incorporate new hardware costing millions of dollars for larger projects. This directly impedes the adoption of new hardware leaving software systems lagging years to decades behind the latest hardware developments, inefficient and open to cyber-attacks.

 

We are developing data-centric hardware and system architectures as well as building the software platform needed to optimise existing codes on dynamically-changing systems. By bringing together established open-source standards with innovations in mathematics, computer science, and engineering, we will define a simplified standard infrastructure for the future development of computation. This requires a deep understanding of existing hardware architectures to best exploit the unique benefits of each system and interface seemingly incompatible technologies.

Working alongside an interdisciplinary team, you will bring your knowledge and development skills to develop the mathematics and software required to develop and deploy these diverse systems.

 

who should apply

You bring broad technical knowledge (see below) at a Doctoral level or Masters with industry experience and are comfortable exploring computing at every level of abstraction. You’re highly collaborative and able to think creatively to solve problems, not constrained by conventional thinking. You should be curious, always asking why and actively enjoy building a network around the problems and opportunities that you go after.

We’re looking for a candidate with experience in the following:

●  Compiler technology (LLVM, JIT compilation, intermediate representations, interpretation)

●  C, C++ and related machine learning packages (mlpack, TensorFlow, Dlib)

●  Graph theory (topological graph theory, directed graphs, computational tools)

●  Hardware-specific APIs (ex. CUDA) as well as cross-platform APIs (ex. OpenCL) would be an advantage but not required.

 

 

our offer

Taking a Co-founder role at DSV is a fantastic opportunity to develop concepts for, and launch your own startup. Working with us, you’ll have access to the systems and environment to guide your thinking, and we’ll even pay you a monthly salary to start your own company and support you in building the founding team and developing early data to land your first customers and investors. After a 3-6 month period, we will support you in taking the role of CEO or CTO of the company we design together and spin out with a pre-seed investment from DSV.

Compared to other Entrepreneur in Residence programmes, DSV’s is friendly to individuals with no previous founder experience and comes with a commitment from us to support your company to make a real impact in the market.

No prior idea or IP required.

For decades hardware developers have raced against each other to accelerate computing by shrinking transistor size and increasing processor density but we are quickly approaching a fundamental limit. New architectures are emerging as an alternative to capitalise on task parallelism and optimised hardware layouts for a small class of functions such as those used in machine learning. Alongside this, completely novel systems (neuromorphic, photonic, quantum) are being developed independently without a way to interoperate with each other and existing architectures.

However, this processor-centric model used ubiquitously for the past 75 years is fundamentally incompatible with the current data-driven landscape due to the outdated view of information and storage. The software developed for these rigid systems is completely inflexible requiring an entire team of software developers working years to incorporate new hardware costing millions of dollars for larger projects. This directly impedes the adoption of new hardware leaving software systems lagging years to decades behind the latest hardware developments, inefficient and open to cyber-attacks.

 

We are developing data-centric hardware and system architectures as well as building the software platform needed to optimise existing codes on dynamically-changing systems. By bringing together established open-source standards with innovations in mathematics, computer science, and engineering, we will define a simplified standard infrastructure for the future development of computation. This requires a deep understanding of existing hardware architectures to best exploit the unique benefits of each system and interface seemingly incompatible technologies.

Working alongside an interdisciplinary team, you will bring your knowledge and development skills to develop the mathematics and software required to develop and deploy these diverse systems.

 

who should apply

You bring broad technical knowledge (see below) at a Doctoral level or Masters with industry experience and are comfortable exploring computing at every level of abstraction. You’re highly collaborative and able to think creatively to solve problems, not constrained by conventional thinking. You should be curious, always asking why and actively enjoy building a network around the problems and opportunities that you go after.

We’re looking for a candidate with experience in the following:

●  Compiler technology (LLVM, JIT compilation, intermediate representations, interpretation)

●  C, C++ and related machine learning packages (mlpack, TensorFlow, Dlib)

●  Graph theory (topological graph theory, directed graphs, computational tools)

●  Hardware-specific APIs (ex. CUDA) as well as cross-platform APIs (ex. OpenCL) would be an advantage but not required.

our offer

Taking a Co-founder role at DSV is a fantastic opportunity to develop concepts for, and launch your own startup. Working with us, you’ll have access to the systems and environment to guide your thinking, and we’ll even pay you a monthly salary to start your own company and support you in building the founding team and developing early data to land your first customers and investors. After a 3-6 month period, we will support you in taking the role of CEO or CTO of the company we design together and spin out with a pre-seed investment from DSV.

Compared to other Entrepreneur in Residence programmes, DSV’s is friendly to individuals with no previous founder experience and comes with a commitment from us to support your company to make a real impact in the market.

No prior idea or IP required.

Interviews ongoing

Interviews ongoing

current founders

At DSV Brock is working on accelerated computing hardware that overcomes the limitations and inefficiencies in conventional computing. This currently spans extremely low-power machine learning accelerators, quantum computing, and cybersecurity to protect these systems. His background and experience spans across photonics, device engineering, cybersecurity, mathematics, and distributed networks.