What to expect
Emteq is situated in Brighton, close to the heart of the South Downs in East Sussex, England. Our office and labs are located at the University of Sussex Innovation Centre. With panoramic views of the South Downs, and Brighton Beach just 15 minutes away, our office makes for a inspiring environment to work in.
Our office is extremely convienient to reach via train, bus, car or even cycle (if you can manage the hill!) with easy connections to Gatwick Airport or London.
You will be entitled to 30 days annual leave, and can work from home or join us in the office. We are fairly flexible when you turn up to work, so no need to panic if you can't bear the 9am-5pm grind.
What we do
We are focusing on harnessing human emotions and expressions to incorporate them into digital environments. The benefits of this are significant for:
Healthcare: social interaction skills training e.g. in autism, mental health therapies e.g. PTSD
Entertainment: shared virtual experiences, improve human-computer interaction
Business: remote collaboration
Gaming: interactive avatars, and response gameplay
Emteq believes that face to face interaction is at the core of our interpersonal relationships. Building a platform to transcend time and space is hard, but will impact on many lives
Working at Emteq is multidisciplinary, engaging you in a variety of projects to stretch your capabilities
- Creative - imagine new technologies for shared experiences and for a positive impact
- Challenging - intellectually stimulating work at the cutting edge of human-computer interaction
- Stimulating - academics can publish in journals and present at conferences
- Flexible - work from anywhere- we are not constrained by geography
- Personal - help us realise your goals e.g. work/ life balance, academic, developing IP
- Healthy - we encourage exercise and a healthy lifestyle (plus occasional treats!)
- Lean - we've achieved a lot since founding. Build, measure and learn
Interested? Send an up to date CV and covering note to email@example.com
MACHINE LEARNING SCIENTIST WITH DSP BACKGROUND
Collaborate with senior machine learning researchers and engineers. Provide technical expertise to address supervised and unsupervised learning problems in an applied research and development environment. Develop & deploys modern machine learning and statistical methods (e.g. CART and Random Forests, clustering and classification algorithms, Bayesian models, neural nets, SVM etc.) for finding patterns/models from biosignals. Familiarity with large data sets, cloud based development and deployment, open source practices and frameworks and experience in putting an application into production is desirable.