Applied Physicist On Event Reconstruction

**Company Description**
**Job Description** Introduction**

You will join the Next Generation Trigger (NGT) initiative at CERN. As part of our commitment to pushing the boundaries of scientific exploration, we are embarking on the Real-time Reconstruction Revolution (R³ - Rcube) project. This initiative aims to rethink the traditional CMS Phase-2 High-Level Trigger (HLT) reconstruction system by leveraging heterogeneous computing resources, adopting contemporary development methodologies and integrating modern AI-driven techniques.

**Functions**

You will** **take on key responsibilities in the Real-time Reconstruction Revolution (R³ - Rcube) project. You will dive into the formidable challenges of achieving nearly two orders of magnitude acceleration in the overall reconstruction time, including particle flow, jets/MET, muon, taus, and E/Gamma for the CMS high-level trigger processing step. Your activities will include:

- Conduct a critical assessment of the current high-level trigger reconstruction performance, and design and develop innovative approaches that push the boundaries of existing methodologies. Implement advanced algorithms, incorporating GPU acceleration, heterogeneous architectures, and AI technologies to enhance event reconstruction at the HLT.
- Collaborate closely with NGT Task leaders to leverage their progress, align their efforts with your requirements, and ensure consistent and reliable contributions to developing the CMS NGT high-level trigger project.
- Develop and oversee a comprehensive validation suite and evaluating the physics and computational prowess of the reconstruction algorithms run during high-level trigger processing.
- Collaborate closely with the team, you will integrate these cutting-edge algorithms into the existing CMS High-level trigger reconstruction software.
- Assist various team members in adopting the novel reconstruction algorithms developed and their products into their specific HLT paths.
- In this dynamic role, you will not only tackle the present challenges but also provide crucial technical guidance and mentorship to propel the project toward creating the CMS HLT community of tomorrow, a necessity in anticipation of the HL-LHC era.
- Additionally, you will supervise doctoral students and fellows ensuring a well-rounded and impactful contribution to the broader research objectives**.**

**Qualifications**
PhD or equivalent relevant experience in the field of Physics or Computer Science or a related field.

**Experience**:
Required experience in the following areas:

- Experience in event reconstruction and software development for the High-Level Trigger at a high energy physics (HEP) experiment.
- Experience in C++ programming, including the latest C++ standards (C++17 or later).
- Using modern software development tools: containerised environments, debugging tools, profiling tools, source code management (git), merge requests, CI/CD, issue tracking, and documentation.

Nice to have experience:

- Good knowledge of the conditions required for optimal event reconstruction in high-energy physics experiments, including how these conditions are derived and their impact on the overall physics outcomes of the reconstruction.
- Familiarity with deep learning frameworks.

**Technical competencies**:

- Simulation, design and development of trigger, data acquisition chains: expertise in designing and implementing HLT menus and trigger paths for optimised real-time performance.

**Behavioural competencies**:

- Solving problems: addressing complex problems by breaking them down into manageable components. Finding the information needed to solve problems; making objective judgments based on all the facts available. Being open to original ideas and creative options by which to address issues; continually driving change by seeking new ways to improve outcomes.
- Learning and sharing knowledge: keeping up-to-date with developments in own field of expertise and readily absorbing new information. Taking steps to expand knowledge in other areas of expertise beyond own field. Sharing knowledge and expertise freely and willingly with others; coaching others to ensure knowledge transfer.
- Working in teams: working well in groups and readily fitting into a team; participating fully and taking an active role in team activities. Cooperating constructively with others in the pursuit of team goals; balancing personal goals with team goals. Seeking to help other team members when own work is done; supporting others.
- Demonstrating flexibility: demonstrating openness to new ideas and situations. Readily absorbing new techniques and working practices; proposing new or improved ways of working. Actively participating in the implementation of new processes and technologies.

**Language skills**:
Spoken and written English: ability to understand and speak the language in professional contexts.
**Additional Information** Eligibility and closing date**:
**Employment Conditions**