Are you a professional with vast experience in Machine Learning? Do you have experience in Signal Processing? Do you enjoy working in a challenging international environment? If so, CMRE is looking for you!

POST CONTEXT

This is a position within the Centre for Maritime Research and Experimentation (CMRE), an organization of the North Atlantic Treaty Organization (NATO).

CMRE is an established, world-class scientific research and experimentation facility that organizes and conducts scientific research and technology development, centred on the maritime domain, delivering innovative and field tested Science & Technology (S&T) solutions to address defence and security needs of the Alliance.

The position is within the Research Division (RD), which leads the development of CMRE’s scientific strategy and through its capability in ocean sensing, numerical modelling, big data analytics, artificial intelligence (AI), data fusion, signal processing, and autonomy, delivers the Centre’s S&T goals while maintaining CMRE’s reputation within the scientific community.

The Research Division is composed of the following Departments:

1. Antisubmarine Warfare (ASW)

2. Naval Mine Countermeasures (NMCM)

3. Data & Environmental Knowledge and Operational Effectiveness (D-EKOE)

4. Maritime Unmanned Systems Enablers (MUSE)

5. Climate Change and Security (CCAS)

This position is within the D-EKOE Department and contributes to the Data Knowledge and Operational Effectiveness project within the Data and Environmental Knowledge and Operational Effectiveness (D-EKOE) Programme. This position is for an A1 (G11) Scientist.

PRINCIPAL DUTIES 

We are seeking a talented Machine Learning/Signal Processing Scientist to join our team in the Research Department at CMRE. This role requires a strong research background and expertise in both the signal processing and machine learning fields. As a Machine Learning/Signal Processing Scientist, you will be tasked with developing and implementing cutting-edge techniques at the boundary between machine learning and signal processing to solve complex problems using extensive datasets comprising time-varying and heterogeneous surveillance information. Your primary responsibilities will include developing novel algorithms and models, extracting valuable insights, and providing actionable recommendations to support CMRE’s research objectives pertaining to the innovative concept of Seabed-to-Space Situational Awareness (S3A).

Detailed duties: 

·  Support the DKOE programme of work in the investigation and development of innovative and cutting edge scientific research ideas in the area of Machine Learning and Signal Processing applied to the novel concept of Seabed-to-Space Situational Awareness (S3A).

·  Develop and implement advanced and novel machine learning/signal processing algorithms and models to combine, fuse, synthesize and classify heterogeneous sensor/surveillance/geospatial/contextual data.

·  Develop rigorous mathematical understanding/interpretation of the developed machine learning /signal processing algorithms and their performance.

·  Collaborate with researchers and domain experts to identify research questions and design experiments to address them.

·  Stay updated with the latest advancements in signal processing, machine learning, target tracking, data fusion and related fields, and apply relevant methodologies to research projects.

·  Participate in interdisciplinary research teams and contribute to research proposals and publications, both internal (CMRE reports) and external (peer-reviewed scientific publications).

·  Present research findings at conferences, workshops, and internal meetings.

·  Work closely as required with projects outside of the DKOE Programme.

·  Support the organization and execution of NATO workshops and conferences; the establishment of Multi-National Projects as relevant in the fields of Underwater Critical Infrastructure (UCI) monitoring; the development of proposals for external funding including from National Naval R&D funding agencies, National or NATO Multi-National projects, or from European funding mechanisms.

SPECIAL REQUIREMENTS AND ADDITIONAL DUTIES 

a. Flexibility Clause 

The incumbent may be required to perform other related duties as directed. 

All other related duties should correspond with the required competencies for the job. 

b. Deployment/Travel 

The incumbent may be required to perform his/her duties onboard Centre or chartered vessels. The incumbent may be required to undertake TDY assignments within and outside NATO boundaries.

ESSENTIAL QUALIFICATIONS 

a. Professional/Experience 

• Strong background in signal processing, statistical analysis, probability theory and machine learning.
• Solid understanding of research methodologies and experimental design.
• Excellent problem-solving and analytical skills, with the ability to work with heterogeneous and time-varying sources of data.
• Strong communication skills to present complex research findings to both technical and non-technical audiences.
• Proficiency in programming languages such as MATLAB or Python/R for scientific programming and prototyping.
• Strong attention to detail and commitment to delivering high-quality results.
• Passion for research and innovation in data science and its application to real-world problems.

b. Education/Training

·  MSc in Engineering, Computer Science, Statistics, Mathematics, or a related field and at least 1-year post-MSc experience with a focus on machine learning and signal processing,

Or

·  Ph.D. in Engineering, Computer Science, Statistics, Mathematics, or a related field with a focus on machine learning and signal processing.

c. Language Requirements

A thorough knowledge of one of the two NATO languages, both written and spoken, is essential and some knowledge of the other is desirable.

English SLP 3333

NOTE: Most of the work of CMRE is conducted in the English language.

DESIRABLE QUALIFICATIONS 

• A Ph.D. in the field of Machine Learning, Statistical Signal Processing, or a related subject.
• Excellent knowledge of machine learning methods such as Deep/Adversarial/Recurrent/Generative neural networks.
• Experience with machine learning libraries and frameworks (e.g., TensorFlow, scikit-learn, PyTorch) for model development and deployment.
• Experience with data from maritime surveillance sensors (such as radar, sonar, synthetic aperture radar, Automatic Identification System, etc.).
• Experience with the Model-Based Machine Learning concept.
• Publication record in peer-reviewed conferences or journals.
• Experience working in multi-disciplinary and international environments.

COMPETENCIES 

The successful candidate possesses the following competencies / personal attributes:

• Excellent communication skills, both oral and written – able to communicate at all levels;
• Very good interpersonal skills. Solicits inputs and encourages others;
• Innovative and driven. Always displaying sound judgement;
• Excellent time management and organizational skills.

All CMRE personnel are expected to conduct themselves in accordance with the current NATO Code of Conduct agreed by the North Atlantic Council (NAC), and thus display the core values of integrity, impartiality, loyalty, accountability, and professionalism.

REMARKS 

The duties are performed in an office, laboratory, workshop environment or on-board Centre ships.

About Us:

The Centre for Maritime Research and Experimentation (CMRE) is part of the NATO Science and Technology Organization (STO).  The mission of the STO is to help position both national and NATO science and technology investments as a strategic enabler and technology advantage for the defence and security posture of NATO Allies and partners. The Centre conducts scientific research and technology development and delivers innovative field-tested S&T solutions to address the defence and security needs of the Alliance. CMRE has more than 60 years of experience and has produced a cadre of leaders in ocean science, modelling and simulation, acoustics and other disciplines, as well as producing critical results and understanding that have been built into the operational concepts of NATO and the Nations.

What we offer:

• Salary (Pay Basis): 4,478.79 (EUR) Monthly*

*Salary value as per 2023. Subject to future adjustments in accordance with North Atlantic Council decisions.

• Grade ABCL grade A1 / NATO grade G11
• A world class research facility located in the sea port of La Spezia, Italy supported by two specialised research vessels.
• An exciting place in which to work situated at an ideal location, the port of La Spezia, Italy, enabling synergy with regional and global academic institutes and industry.
• Salary and conditions of employment will be in accordance with the NATO Civilian Personnel Regulations (NCPR), which includes a rewarding salary and a comprehensive system of allowances, supplements and insurances to support families and, in case of expatriated staff, offers an interesting “expatriate” package.
• A generous annual leave and, (where eligible) home leave.
• The successful candidate will be offered a three years’ definite duration contract which may be renewed for subsequent periods subject to business needs, satisfactory performance and the need to rotate skills and talent within the Organization.
• Applicants who prove to be competent for the post but who are not successful in this competition may be offered an appointment to another post of a similar nature, which might become vacant in the near future, albeit at the same or a lower grade, provided they meet the necessary requirements.

 Our recruitment process:

• Please note that we can only accept applications from nationals of NATO member countries;
• Applications (including the most relevant publications, the diplomas – stating the highest level of education – and a CV) for this vacancy are to be submitted using the E-recruitment system;
• Appointment will be subject to receipt of a security clearance (provided by the national Authorities of the selected candidate) and approval of the candidate’s medical file by the CMRE Medical Adviser.

 Additional information: 

·    CMRE values diverse backgrounds and perspectives and is committed to recruiting and retaining a diverse and talented workforce. We welcome applications of nationals from all Member States and strongly encourage women to apply.

·     Selected candidates are expected to be role models of integrity, and to promote good governance through ongoing efforts in their work.