University Institute for Computer Research
Organisation/Company Universidad de Alicante Department University Institute for Computer Research Research Field Computer science » Other Researcher Profile Other Profession Positions Research Support Positions Country Spain Application Deadline 17 Sep 2025 - 23:
59 (Europe/Madrid) Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 4 Sep 2025 Is the job funded through the EU Research Framework Programme? NextGenerationEU Reference Number INREIA/2024/151 Is the Job related to staff position within a Research Infrastructure? No
Offer Description
Applications are invited by the University of Alicante President to create a pre-shortlist of candidates for the recruitment of research staff (contract type:
open-ended contract;
job category:
senior technologist) to collaborate with the funded line of research “Machine learning methods and models for acoustic and sound signals”. Reference:
I-PAS-55/25
Pursuant to the provisions of the regulations governing calls for applications of research staff to cover contractual positions assigned to research projects, available at the following website address:
approved by the Governing Council of 22 December 2009 (BOUA of 15 January 2010), and with instructions of the University of Alicante Offices of the Registrar and the Comptroller, which establish the mandatory use of electronic means for the submission of applications, documentation, payment of fees, communications, notifications and all other procedures of the selection procedures for the temporary contractual administrative and services staff and research staff and other general applicable regulations, the University of Alicante calls for applications to create a pre-shortlist of candidates for the recruitment of research staff in accordance with the following terms and conditions:
First. General terms.
1.1. The purpose of this call is to create a pre-shortlist of candidates for the recruitment of research staff (job category:
senior technologist) in the framework of the projects included in the funded line of research “Machine learning methods and models for acoustic and sound signals”.
1.2. Unit in charge of the line of research:
University Institute for Computer Research.
1.3. The first project in which the successful applicant(s) will collaborate, as well as the number of available vacancies and the characteristics of the job role, are set out in the annex hereto. At the end of the duration of this first project or its budgetary availability for this recruitment process, the successful applicant(s) may join other projects within the same line of research.
1.4. The panel in charge of the recruitment process may decide to create a talent pool including candidates whose applications were unsuccessful but who participated in all the stages of the recruitment process and, where applicable, passed the relevant test. In such a case, the panel may set a minimum score for candidates to be placed in the pool.
The pool will list candidates in descending order of score. Candidates in the pool may be contacted if a successful applicant does not accept the position offered or, after accepting it, is on a temporary leave of absence, resigns or is dismissed. They may also be contacted to cover additional needs of the project (or of other projects within the same line of research), as long as the tasks to be fulfilled are related to the job profile specified in this call for applications.
If candidates are offered a position, they will be contacted in the order listed in the pool.
The candidate(s) selected for the job position(s) will be added to the talent pool at the end of their contract(s). Their position on the list will be determined by the score they achieved during the recruitment process.
In accordance with the provisions of the agreement of the Governing Council of 27 January 2022, which approves the University of Alicante 4th Plan for equal opportunities between women and men, and with article 61.2. f) of Valencia Government Law 4/2021, of 16 April, of the Valencian Civil Service, it is hereby stated that the percentage distribution in the contractual job vacancies of senior technologist for research projects is 54.65%for women and 45.35% for men, so there is no under-representation of either sex in this job category.
Second. Requirements for applicants.
Compliance with the requirements listed below must always refer to the date of expiry of the deadline for the submission of applications and must be maintained until the date of entering into the contract.Applicants must:
2.1. Hold or be in the process of obtaining a 1st-cycle undergraduate degree, an engineering technology degree, an architectural technology degree or equivalent. In the case of qualifications obtained overseas, a statement of comparability or equivalent must be provided. Applicants who are not in possession of the degree certificate must provide proof of payment of the diploma issuing fee or submit an academic certificate stating that they have completed all the studies leading to the award of said certificate.
Under no circumstances will qualifications corresponding to the MECES level of official 4-year undergraduate degrees—belonging to academic systems prior to the European Higher Education Area regulated by Royal Decree 889/2022, of 18 October, in accordance with the provisions of the fourth additional provision of the aforementioned Royal Decree—be considered as qualifications equivalent to MECES undergraduate degrees. Likewise, holding a Master’s degree, a 1st-cycle undergraduate degree,a 1st-cycle engineering technology degree, a 1st-cycle architectural technology degree will not be considered equivalent.
PhD or Master’s degrees do not, in themselves, constitute qualifications that qualify for access to public employment.
2.2. Have Spanish nationality or be in one of the situations listed in article 57 of Royal Legislative Decree 5/2015, of 30 October, which approves Primary Statute of Public Employees consolidated text (BOE of 31 October). In the case established in point 4 of this article, when legal residence in Spain is required, candidates must hold it at the time of entering into contract.
2.3. Have a good command of any of the official languages of the Valencia Region for the performance of the job.
2.4. Be at least 16 years of age and not be over the maximum age for compulsory retirement.
2.5. Possess the physical and mental capacities and aptitudes that are necessary for the performance of the relevant duties and tasks, for which, prior to entering into contract, a medical certificate must be provided proving the said capacities and aptitudes. For this purpose, the examinations may be carried out through the existing medical services of the University of Alicante Occupational Health and Safety Service.
2.6. Not be disqualified by final judgement or as a result of having been dismissed for disciplinary reasons to perform duties similar to those of the relevant professional category. Nationals of other countries must not be disqualified or in an equivalent situation, nor have been subject to a disciplinary or equivalent punishment that prevents access to public employment in the same terms in their own country.
If an applicant, at any point during and before the completion of the recruitment process, no longer meets all the necessary conditions, they will be required to file a request to withdraw from the process. Otherwise, as soon as it is detected that they do not comply with all the requirements, they will be excluded from the process.
Third. Submission of applications.
By submitting their application, candidates confirm that the information provided in the application is true and that they meet all the requirements set out in the call for applications. They also undertake to provide proof that the information contained in the application is true and correct.
Any supporting documents submitted in a language other than those with official status in the Valencia Region must be accompanied by a sworn translation. Otherwise, said supporting documents may be excluded or not considered.
Merits for which no valid proof has been provided by the deadline for candidates to correct their applications after publication of the provisional list of accepted and rejected candidates (fourth section of the call) will not be taken into account.
At any point during the process, candidates may be required to present the originals of the submitted documents and, where applicable, the sworn translation of said documents.
Sixth. Two-stage selection system:
Merit-based assessment and personal interview. The interview may be recorded.
Applicants of Spanish nationality must prove their identity by presenting their Spanish ID, passport, driving licence or, where applicable, a document issued by a police station that contains their Spanish ID number. Applicants who are not Spanish nationals must prove their identity by presenting a document issued by the relevant authorities of their country of origin or residence;
the document must be a valid proof of identity, age and nationality. Copies or photocopies of said documents are not accepted under any circumstances.
The panel may decide to create a talent pool including candidates whose applications were unsuccessful, in accordance with section 1.4 of this call for applications.
ANNEX:
PURPOSE OF CALL I-PAS-55/25 AND JOB PROFILE
Project INREIA/2024/151 funded by the Valencia Region Government’s Department of Innovation, Industry, Trade and Tourism and by the European Union’s Next Generation Programme / Spain’s Recovery, Transformation and Resilience Plan
1. First project in which the successful applicants will collaborate:
1.1. Name of the project:
“A multimodal, multiagent platform for optimising the purchasing process”.
1.2. Reference:
INREIA/2024/151.
1.3. Funding agency:
Valencia Region Government’s Department of Innovation, Industry, Trade and Tourism.
1.4. Co-funding agency:
European Union’s Next Generation Programme / Spain’s Recovery, Transformation and Resilience Plan.
1.5. Dept. / Institute:
University Institute for Computer Research.
2. Number and features of vacancies.
2.1. Entering into contract, as well as its terms and conditions, will be subject to the receipt of the funding for the project from the relevant agencies, i.E. the Valencia Region Government’s Department of Innovation, Industry, Trade and Tourism and the European Union’s Next Generation Programme / Spain’s Recovery, Transformation and Resilience Plan.
2.2. Number of job vacancies:
two.
2.3. Job position:
senior technologist.
2.4.Working hours:
full-time position, morning/afternoon sessions.
2.5. Remuneration:
€2,200 gross/monthly plus two extra payments of the same amount as the monthly remuneration, or a proportional part for periods of less than one year.
2.6. Tasks to be carried out:
* Designing conversational flows for smart agents based on large language models (LLMs).
* Integrating external tools using APIs.
* Refining interaction prompts with language models, adjusting instructions, examples and formats to ensure the model is aligned with the defined objectives, controlling the consistency, relevance and style of the generated answers.
* Designing and applying context engineering strategies to optimise the input of contextual information into the models, managing prompt length and structure to find a balance between computational costs and answer quality.
* Designing conversational agents with support for standardised communication protocols, such as A2A (Agent-to-Agent), MCP (Model Context Protocol), ACP (Agent Communication Protocol) and AG-UI (Agent–User Interface Protocol), focusing on the management of concurrent agent-to-agent or agent-user interactions and calls.
* Deploying and monitoring conversational agents and models on cloud platforms, including Amazon Web Services (AWS) and Microsoft Azure, configuring services, execution environments and systems to monitor performance and use.
3.1. Official academic qualifications (maximum 2 points). The following qualifications will be considered for this job vacancy:
* Undergraduate degree in Computer Engineering, in Multimedia Engineering, in Robotics Engineering, in Artificial Intelligence Engineering, in Sound and Image Engineering in Telecommunications or in Telecommunications Engineering (Spanish MECES level 2 or EQF level 6), or any other degree with equivalent content.
* Official Master’s degree in Computer Engineering, in Artificial Intelligence, in Data Science, in Development of Web Applications and Services, in Software Development for Mobile Devices or in Telecommunications Engineering (Spanish MECES level 3 or EQF level 7), or any other official Master’s degree with equivalent content.
3.2. Experience (maximum 3 points):
performance of tasks and activities, by means of an employment contract, in any field or administrative relationship, excluding teaching activities, will be assessed at the rate of 1 point per full year, or a proportional part per full month for periods of less than a year, related to the tasks to be carried out and to the job profile (sections 2 and 3 of this annex), as well as to:
* Natural language processing (NLP), using tools or libraries such as SciPy and NLTK.
* Advanced prompting strategies for LLMs, including chain-of-thought (CoT) and tree-of-thoughts (ToT) prompting.
* LLM fine-tuning techniques, including SFT (supervised fine-tuning), PEFT (parameter-efficient fine-tuning), instruction fine-tuning and RLVR (reinforcement learning with human feedback).
* Deployment, operation and monitoring of LLM-based solutions through tools such as AgentOps
* Use of platforms for designing smart agents, such as LangChain, CrewAI, AutoGen or Semantic Kernel.
* Application of retrieval-augmented generation (RAG) techniques and use of vector databases like Pinecone, Qdrant, Chroma, FAISS or Pgvector.
* Use of traceability and observability tools, such as Langfuse, Phoenix or OpenTelemetry.
* Implementation of agent-to-agent communication protocols, like MCP, A2A or ACP.
* Deployment of LLM-based solutions on cloud platforms, including Amazon Web Services (AWS) or Microsoft Azure.
* Use of language models such as OpenAI GPT, Anthropic Claude, Google Gemini or Meta LLaMA.
3.3. Additional education (maximum 3 points). Qualifications related to the tasks to be carried out and to the job profile (sections 2 and 3 of this annex), as well as to:
* Natural language processing (NLP), using tools or libraries such as SciPy and NLTK.
* Advanced prompting strategies for LLMs, including chain-of-thought (CoT) and tree-of-thoughts (ToT) prompting.
* LLM fine-tuning techniques, including SFT (supervised fine-tuning), PEFT (parameter-efficient fine-tuning), instruction fine-tuning and RLVR (reinforcement learning with human feedback).
* Deployment, operation and monitoring of LLM-based solutions through tools such as AgentOps
* Use of platforms for designing smart agents, such as LangChain, CrewAI, AutoGen or Semantic Kernel.
* Application of retrieval-augmented generation (RAG) techniques and use of vector databases like Pinecone, Qdrant, Chroma, FAISS or Pgvector.
* Use of traceability and observability tools, such as Langfuse, Phoenix or OpenTelemetry.
* Implementation of agent-to-agent communication protocols, like MCP, A2A or ACP.
* Deployment of LLM-based solutions on cloud platforms, including Amazon Web Services (AWS) or Microsoft Azure.
* Use of language models such as OpenAI GPT, Anthropic Claude, Google Gemini or Meta LLaMA.
3.3.A) Up to a maximum of 1 point for courses—taken or taught—duly accredited by official centres or organisations, at the rate of 0.01 point per hour of duration up to a maximum of 50 hours per course. In any case, formal education shall be excluded.
3.3.B) Attendance at meetings, seminars and conferences at a rate of 0.01 points per attendance certificate.
3.3.C) Up to a maximum of 2 points for grant-funded training periods at a rate of 0.08 points per full month if they are grants obtained through a public call for applications, and at a rate of 0.04 per full month if grants have been awarded directly to the applicant.
Contractual grants will be assessed considering the duration of the contracts, in the section devoted to the applicant’s experience.
3.4. Academic curriculum vitae:
maximum 5 points. The academic CV related to the tasks to be carried out and to the job profile (sections 2 and 3 of this annex) will be considered.
3.4.A) Academic record of the degrees mentioned in section 3.1 of this annex:
up to a maximum of 2 points, according to this formula:
where M is the average mark obtained in one of the qualifications specified in the aforementioned section 3.1, as it appears in the applicant’s academic record in accordance with the following equation:
were C i states the number of credits of the course and N i refers to the corresponding grade (Pass= 1;
Outstanding = 2;
Distinction = 3;
Distinction with Honours = 4) and nc stands for the number of courses of the relevant degree.
In this section, doctorates will not be taken into account and the highest average mark from among the academic certificates of the other qualifications listed in section 3.1 of this annex will be considered.
3.4.B) Scientific publications (articles, books, journals, etc.) and patents:
up to 1 point.
3.4.C) Collaborations in research activities:
up to 0.50 points.
3.4.D) Communications, papers and posters at conferences, meetings and seminars:
up to 1 point.
3.4.E) Research visits in other centres or organisations carrying out activities directly related to the tasks to be carried out and to the job profile (sections 2 and 3 of this annex):
up to 0.50 points.
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