Doctoral Candidate – Deep Learning for Solidification in Multiphase Flows with Radiative Heat Transfer (MSCA DN COMBINE DC11)

1 Mar 2026
Job Information

Organisation/Company

University of Sarajevo

Department

Faculty of Mechanical Engineering

Research Field

Engineering » Process engineering
Engineering » Thermal engineering
Engineering » Simulation engineering
Engineering » Mechanical engineering
Engineering » Computer engineering
Engineering » Industrial engineering
Mathematics » Applied mathematics
Mathematics » Computational mathematics

Researcher Profile

First Stage Researcher (R1)

Positions

PhD Positions

Application Deadline

30 Apr 2026 - 23:59 (Europe/Sarajevo)

Country

Bosnia and Herzegovina

Type of Contract

Temporary

Job Status

Full-time

Hours Per Week

40

Offer Starting Date

1 Sep 2026

Is the job funded through the EU Research Framework Programme?

Horizon Europe - MSCA

Is the Job related to staff position within a Research Infrastructure?

No

Offer Description

The Faculty of Mechanical Engineering at the University of Sarajevo (UNSA) invites applications for a fully funded PhD position (Reference: COMBINE-DC11) within the Horizon Europe Marie Skłodowska-Curie Actions Doctoral Network (MSCA DN) COMBINE.

The successful candidate will undertake research on:

Deep learning for solidification in multiphase flows with radiative heat transfer

This research combines advanced numerical simulation and artificial intelligence to develop predictive models for high-temperature multiphase flows, with specific relevance to steel casting applications.

The project integrates:

• Computational Fluid Dynamics (CFD) and multiphase flow modeling
• Radiative heat transfer
• Machine learning and reduced-order modeling
• Data-driven optimization for industrial processes

The project is embedded in the ThermoFluids Research Group which develops advanced numerical, experimental and AI-driven methodologies for multiphysics engineering problems.

Problem Definition

The project aims at the development of a self-contained finite volume (OpenFOAM-based) solver for the solidification of multiphase flows with a free surface, including radiative heat transfer through semi-transparent materials, and the utilisation of deep learning algorithms to accelerate computational solutions.

Scientific Objectives

• Develop a self-contained finite volume solver for solidification of multiphase flows at high temperatures with radiative heat transfer through semi-transparent media.
• Investigate the use of deep learning techniques for accelerating multi-physics simulations.
• Employ deep learning algorithms to replace or accelerate computationally demanding components of the solver.
• Evaluate solver performance across different geometries, boundary conditions, and industrially relevant casting configurations.

Expected Results

• Validation of the developed finite volume solver against experimental data and/or benchmark computational studies.
• Validation of the proposed hybrid FV–DL methodology against full-order simulations.
• Quantitative assessment of computational gains (e.g. reduced runtime) achieved through deployment of deep learning algorithms, with controlled and acceptable trade-offs in accuracy.

Envisaged Publications

The research is expected to lead to high-impact journal publications, including:

• Development of an OpenFOAM-based FV solver for solidification in high-temperature multiphase flows (target journals: International Journal for Numerical Methods in Engineering – IJNME).
• Deep learning algorithms for high-temperature multiphase problems (target journals: Computer Methods in Applied Mechanics and Engineering – CMAME / IJNME).
• Deep learning approaches for solidification in multiphase systems (target journals: CMAME / IJNME).

 

 To see all available MSCA DN COMBINE offers please click here .

Where to apply

E-mail

hasecic@mef.unsa.ba

Requirements

Research Field

Engineering » Process engineering

Education Level

Master Degree or equivalent

Research Field

Engineering » Thermal engineering

Education Level

Master Degree or equivalent

Research Field

Engineering » Mechanical engineering

Education Level

Master Degree or equivalent

Research Field

Engineering » Simulation engineering

Education Level

Master Degree or equivalent

Skills/Qualifications

Applicants should have:

• A Master’s degree (or equivalent) in Mechanical Engineering, Computational Engineering, Applied Mathematics, Physics, or a related discipline
• Strong foundation in fluid mechanics and heat transfer
• Experience with numerical methods (CFD or FVM)
• Programming skills (e.g. Python, MATLAB, C++, Fortran)
• Interest in machine learning and data-driven modeling
• Excellent English communication skills
• Ability to work independently and in international teams

Specific Requirements

MSCA Eligibility

To be eligible under MSCA mobility rules, candidates must not have resided or carried out their main activity (work, studies) in Bosnia and Herzegovina for more than 12 months in the 36 months immediately before the recruitment date.

Candidates must not hold a doctoral degree at the time of recruitment.

During the doctoral project, the candidate will undertake the following international secondments:

• Month 19 (1 month) – TATA Steel (Sweden): Exposure to industrial casting processes and validation needs
• Month 28 (4 months) – CIMNE (Spain): Integration of multiphysics solvers with reduced-order modeling (ROM) techniques
• Month 36 (1 month) – KTU (Lithuania): Advanced data analysis and validation methodologies

Languages

ENGLISH

Level

Excellent

Additional Information
Benefits

Financial Conditions & Benefits

This position is fully funded under the Marie Skłodowska-Curie Doctoral Network COMBINE and includes a competitive financial package in accordance with MSCA 2026–2027 funding rules. Final financial terms will be specified in the employment contract, with contributions applied according to the Country Correction Coefficient (CCC).

Indicative monthly (gross) MSCA contributions:

• Living allowance: approximately €4,010 per month (gross), adjusted by the MSCA CCC for Bosnia and Herzegovina
• Mobility allowance: approximately €710 per month
• Family allowance (if applicable): approximately €660 per month

These figures are based on the Horizon Europe MSCA 2026–2027 Work Programme.

In addition to MSCA financial support, as an employee of UNSA, you will receive:

• Full social and employment benefits in accordance with Bosnia and Herzegovina labour law
• Health and pension coverage
• Support for professional development (workshops, training, conferences)
• Access to research facilities, computing resources, and library services
• Support for international collaborations and secondments within COMBINE

Work Environment

The University of Sarajevo is Bosnia and Herzegovina’s leading academic institution, offering:

• A vibrant international research community
• Access to academic and industrial partners across Europe
• A multidisciplinary training environment within MSCA DN COMBINE
• Participation in courses and workshops tailored to doctoral researchers

Sarajevo is a dynamic European capital with a rich cultural heritage and a growing innovation ecosystem, offering an excellent living environment for international researchers.

Selection process

Application Procedure

Applicants should submit the following documents in PDF format:

• Curriculum Vitae (including academic transcripts)
• Motivation letter
• Contact details of two academic referees

Applications should be sent to:

Prof. Amra Hasečić
University of Sarajevo, Faculty of Mechanical Engineering
Email:hasecic@mef.unsa.ba

e-mail subject line: Application – COMBINE-DC11

Recruitment Timeline

• 30 April 2026 – Deadline for applications (with possible extension of up to one month)
• 7 May 2026 – Notification of shortlisted candidates invited for interview
• 26 June 2026 – Completion of interviews
• 30 June 2026 – Formal offer and commitment of selected candidates
• 1 September 2026 – Recommended starting date
• 1 November 2026 – Latest possible starting date

Additional comments

Knowledge of Bosnian/Croatian/Montenegrin/Serbian (BCMS) will be considered an asset.

Work Location(s)

Number of offers available

1

Company/Institute

ThermoFluids Research Group, Department for Process and Environmental Engineering, Faculty of Mechanical Engineering UNSA

Country

Bosnia and Herzegovina

State/Province

Sarajevo

City

Sarajevo

Postal Code

71000

Street

Vilsons Lane

Contact

State/Province

Bosnia and Herzegovina

City

Sarajevo

Website

https://www.unsa.ba
https://www.mef.unsa.ba/

Street

Obala Kulina bana 7/II

Postal Code

71000

E-Mail

hasecic@mef.unsa.ba

STATUS: EXPIRED

• X (formerly Twitter)
• Facebook
• LinkedIn
• Whatsapp
• 
  More share options
  • E-mail
  • Pocket
  • Viadeo
  • Gmail
  • Weibo
  • Blogger
  • Qzone
  • YahooMail