6 Laboratory Intern jobs in Australia

We are a world class research-intensive university. We deliver teaching and learning of the highest quality. We play a leading role in economic, social and cultural development of the North East of England. Attracting and retaining high-calibre people is fundamental to our continued success.

Salary

Research Assistant - £28,756 to £0,497 per annum

Research Associate 1,406 to 3,309 with progression to 0,927 per annum

Closing Date : 15th February 2022

The Role

This exciting Research Assistant/Associate position is for a Machine Learning expert who will join a multi-national European project. The candidate will become a member of the ICOS Research Group ( and work under the direction of Prof. N. Krasnogor and Dr E. Torelli.

During the project, you will have the opportunity to investigate, develop and apply machine learning techniques, in collaboration with consortium partners, to datasets derived from real-world experimental data.

You will have the opportunity to contribute towards data sets definition, federation and collection; data capture from instruments and experiments; data wrangling, etc. You will create deep learning tools for predicting experimental outcomes and process optimisation. You will have the opportunity to work on an integrated loop in which every round of machine learning prediction can be used to improve the experimental activities carried out by the consortium and hence gather more and better data for the next round of iterations.

You will work towards the milestones set out for Newcastle within this multi-national project. Furthermore, the researcher will keep excellent records of all computational experiments, procedures, protocols, workflows and outcomes, enabling reuse, interpretation by team members and delivery of project milestones. You will be responsible for reporting to the consortium and publishing the work (either as papers or software or both).

We are seeking a dedicated individual with demonstratable communication skills, a consummate team player with the ability to produce actionable machine learning workflows of a high quality at an experienced level. We are looking for a committed individual with exceptional talent. As part of our drive to build a stellar team, the final selection of short-listed candidates will involve (a) a pre-interview practical exercise, (b) a remote video interview, (c) a post-interview exercise and (d) a collection of at least 2 satisfactory reference letters. Shortlisted candidates who complete this process (whether successful or not will have an inconvenience expense paid). Candidates who are not prepared to fulfil steps (a, b, c & d) should not apply. Candidates close to completing their PhDs can apply.

This position is available on a full time, fixed term basis, to start immediately and is tenable for 24 months from the start date, or until the official project end date, whichever is soonest.

Relocation to the United Kingdom is not required and remote applicants are welcome to apply.

For any informal enquiries please contact Prof. Natalio Krasnogor, Professor of Computing Science and Synthetic Biology via email:

Key Accountabilities

Design, implement, test and debug the entire integrated machine learning workflow for the consortium Establish the data sets strategy for the consortium including data sets definitions, data capture, federation and collection architecture, data wrangling, etc. Utilise state-of-the-art machine learning toolkits to bootstrap the ML infrastructure and -if appropriate- create new toolkits for unmet challenges Development of repeatable computation protocols for the above demonstrating the successful operation of the consortium’s ML workflow, including regular software releases via a version control system Contribution to writing scientific papers and project reports Oral presentations at scientific meetings, workshops, conferences as well as business & consortium meetings The Person (Essential)

Knowledge, Skills And Experience

Demonstrable experience establishing machine learning infrastructures from data acquisition to actionable ML predictions Demonstrable experience with deep learning and other machine learning techniques Demonstrable experience with state-of-the-art ML software packages Demonstrable experience with cloud computing infrastructure for machine learning applications Demonstrable software engineering experience including version control Desirable

Demonstrable experience publishing in peer-reviewed outlets Demonstrable experience in laboratory automation Demonstrable experience applying ML to bioinformatics, chemoinformatics, nanotechnology or biotechnology Demonstrable experience working with scientists and engineers across different discipline Presentation of work at technical as well as more general stakeholders meetings Attributes and Behaviour

Excellent communication skills both oral and written (e.g software documentation, technical reports, papers, presentations, pitches, etc) Capacity for original thought and independent action Enthusiastic, hardworking and goal-setter Ability to interact with people from different disciplines and, while working as part of a team, drive machine learning infrastructure forward Punctual and generally dependable Qualifications

PhD awarded (essential) in computing science, engineering, mathematics or a very closely related discipline (Associate Level) Candidates must be able to spend time away from Newcastle visiting collaborators' labs and attending business meetings outside Newcastle, including international conferences and industrial partners The School/Institute holds a bronze Athena SWAN award in addition to the University’s silver award in recognition of our good employment practices for the advancement of gender equality. The University also holds the HR Excellence in Research award for our work to support the career development of our researchers, and is a member of the Euraxess initiative supporting researchers in Europe.

Newcastle University is committed to being a fully inclusive Global University which actively recruits, supports and retains staff from all sectors of society. We value diversity as well as celebrate, support and thrive on the contributions of all our employees and the communities they represent. We are proud to be an equal opportunities employer and encourage applications from everybody, regardless of race, sex, ethnicity, religion, nationality, sexual orientation, age, disability, gender identity, marital status/civil partnership, pregnancy and maternity, as well as being open to flexible working practices.

Requisition ID: 6341