Job Information
- Organisation/Company: University of Lleida
- Department: Computer Engineering
- Research Field: Engineering » Computer engineering
- Researcher Profile: First Stage Researcher (R1)
- Positions: PhD Positions
- Application Deadline: 31 Aug 2026 - 23:59 (Europe/Madrid)
- Country: Spain
- Type of Contract: Temporary
- Job Status: Full-time
- Hours Per Week: 37.5
- Is the job funded through the EU Research Framework Programme?: Horizon Europe - MSCA
Offer Description
We invite applications for a fully funded PhD position at Univesity of Lleida, within the Logic & Optimization group, under the supervision of Dr. Carlos Ansótegui. The successful candidate will carry out research at the intersection of propositional satisfiability (SAT), Maximum Satisfiability (MaxSAT), and proof complexity.
Note: We updated the deadline to August 31, 2026.
Where to apply
E-mail: info@cords-dn.at
Requirements
- Research Field: Computer science » Other
- Education Level: Master Degree or equivalent
- Research Field: Mathematics » Mathematical logic
- Education Level: Master Degree or equivalent
Skills/Qualifications
- Master's degree (or equivalent granting access to doctoral studies) in Computer Science, Mathematics, or a closely related field, completed by the starting date.
- Strong background in algorithms, data structures, and computational complexity.
- Solid programming skills in Python and/or C++ (the languages of the Paramita framework the candidate will extend).
- Familiarity with propositional logic; prior exposure to SAT/MaxSAT solving, constraint programming, or proof complexity is an asset but not required.
- Motivation to combine theoretical analysis with solver implementation and experimentation.
Languages: ENGLISH
Level: Excellent
- Research Field: Engineering » Computer engineering
- Years of Research Experience: None
Additional Information
Benefits
Research topic
The Satisfiability (SAT) problem, the first problem shown to be NP-complete, asks whether a Boolean formula in Conjunctive Normal Form has a satisfying assignment and is fundamental to computer science. SAT solvers have improved dramatically over recent decades due to techniques such as non-chronological backtracking and conflict-driven clause learning (CDCL), allowing modern solvers to handle industrial instances with hundreds of thousands of variables and millions of clauses.
More powerful SAT solvers can also improve Maximum Satisfiability (MaxSAT), the optimization version of SAT, which seeks to satisfy as many clauses as possible while distinguishing between hard and soft constraints. SAT-based MaxSAT algorithms repeatedly invoke a SAT solver to test bounds on the optimum. This thesis conjectures that significant progress in core-guided MaxSAT solvers (a family of MaxSAT solvers) requires selecting effective core sequences rather than merely optimizing search within a fixed sequence. Different core sequences can lead to vastly different performance, including exponentially harder instances, making their avoidance essential. In this thesis, we aim to design meta-algorithms that efficiently explore and select favorable core sequences.
Finally, gadgets allow us to transform a SAT instance into a Max2SAT instance for use with MaxSAT solvers. The combination of such gadgets with MaxSAT algorithms can yield proof systems stronger than Resolution. In this thesis, we aim to build on these efforts by offering new insights into generating SAT-to-Max2SAT gadgets that can be exploited more efficiently by MaxSAT solvers.
To demonstrate impact beyond benchmarks, the project will apply these techniques to challenging mathematical and industrial problems, in particular optimization problems arising from interpretable machine learning models. This application aligns with the project's broader objectives on trustworthy AI, where SAT- and MaxSAT-based methods can support the development and analysis of interpretable decision models.
As part of the thesis, the candidate will contribute to and extend Paramita (https://pypi.org/project/paramita/), an extensible open-source framework for building applications around SAT, MaxSAT and related satisfiability technologies. Paramita provides a unified API for interacting with different solvers, supports plugins written in C++ and Python, and includes modelling tools for constructing and solving problems. The algorithms and gadget-generation techniques developed in this thesis will be implemented and released as part of the Paramita ecosystem, ensuring reproducibility and broad availability of the results.
What we offer
- A fully funded 3-year PhD contract funded by The Marie Skłodowska-Curie Actions (MSCA) Doctoral Networks programme Grant Agreement / Confident Data-Driven Decision Support (CoRDS) Ref. 101227512].
- The MSCA provides a total annual employment cost of €54,522.72 for this position, which includes the employer's Social Security contributions. After these contributions are deducted, the estimated annual gross salary is €33,272.28. For researchers with family obligations, the total annual employment cost increases to €62,422.72, with an estimated annual gross salary of €37,986 after employer Social Security deductions. In both cases, the employee's own Social Security contributions and personal income tax (IRPF) are deducted from the gross salary to determine the net salary. These amounts may change if Spanish legislation is updated.
- Enrolment in the doctoral programme in Engineering and Information Technology at University of Lleida.
- A stimulating international research environment with opportunities to attend leading conferences (e.g., SAT, IJCAI, AAAI, CP) and collaborate with international partners.
Eligibility criteria
- Candidates must be eligible for admission to the doctoral programme at University of Lleida (https://www.doctorat.udl.cat/en/doctorands/admissio/).
- Mobility or nationality requirements imposed by the funding programme, if any.
Selection process
Applications will be evaluated by a coordinator designed by the coordinator of the Doctoral Network on the basis of academic record, research fit, and motivation. Shortlisted candidates will be invited to an online interview. committeecoordinator
Additional comments
How to apply
Send the following documents in a single PDF to info@cords-dn.at with the subject "Application DC 10":
- Curriculum vitae.
- Academic transcripts (Bachelor's and Master's).
- Motivation letter (max. 1 page) describing your interest in the topic.
- Contact details of [1–2] referees (or reference letters).
Deadline: 31/08/2026. Informal enquiries are welcome and may be addressed to Carlos Ansótegui (carlos.ansotegui@udl.cat).
Note: We updated the deadline to August 31, 2026.
Work Location(s)
Number of offers available: 1
Company/Institute: University of Lleida
Country: Spain
State/Province: Lleida
City: Lleida
Postal Code: 25001
Street: Jaume II, n 69
Contact
City: Lleida
Website: https://ulog.udl.cat/
Street: Jaume II, 69
Postal Code: 25001
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